Description
Enterprise value (EV), Total enterprise value (TEV), or Firm value (FV) is an economic measure reflecting the market value of a whole business. It is a sum of claims of all claimants: creditors (secured and unsecured) and equityholders (preferred and common).
THE IMPACT OF DERIVATIVES ON FIRM VALUE
CHEE MUN FEI KAM MEI KUAN LAI YEW KEAN POH ENG MING TAN HOAY SHAN
BACHELOR OF FINANCE (HONS)
UNIVERSITI TUNKU ABDUL RAHMAN FACULTY OF ACCOUNTANCY AND MANAGEMENT DEPARTMENT OF ECONOMICS APRIL 2011
THE IMPACT OF DERIVATIVES ON FIRM VALUE
BY CHEE MUN FEI KAM MEI KUAN LAI YEW KEAN POH ENG MING TAN HOAY SHAN
A research project submitted in partial fulfillment of the requirement for the degree of BACHELOR OF FINANCE (HONS) UNIVERSITI TUNKU ABDUL RAHMAN FACULTY OF ACCOUNTANCY AND MANAGEMENT DEPARTMENT OF ECONOMICS APRIL 2011
The Impact of Derivatives on Firm Value
Copyright @ 2011 ALL RIGHTS RESERVED. No part of this paper may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, graphics, electronic, mechanical, photocopying, recording, scanning, or otherwise, without the prior consent of the authors.
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The Impact of Derivatives on Firm Value
DECLARATION
We hereby declare that: (1) This UBFZ3026 Research Project is the end result of our own work and that due acknowledgement has been given in the references to ALL sources of information be they printed, electronic, or personal. (2) No portion of this research project has been submitted in support of any application for any other degree or qualification of this or any other university, or other institutes of learning. (3) Equal contribution has been made by each group member in completing the research project. (4) The word count of this research report is 14590 words.
Name of Student: 1. Chee Mun Fei 2. Kam Mei Kuan 3. Lai Yew Kean 4. Poh Eng Ming 5. Tan Hoay Shan
Student ID: 09 UKB 07265 09 UKB 07267 09 UKB 07270 08 UKB 07752 09 UKB 06707
Signature:
Date: 20 April 2011
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The Impact of Derivatives on Firm Value
ACKNOWLEDGEMENT
First of all, we would like to take this opportunity to acknowledge the contribution provided by various authorities who provided guidelines to help us in completing this research project.
We would like to express our deepest appreciation to our supervisors for this research project, Dr. Maran Marimuthu who has guided us throughout the entire research. His expertise, excellent guidance and invaluable comments or suggestion greatly assisted us for the completion of the research project. In addition, we also would like to thank Mr. Ng Kean Kok who is our second examiner for providing useful advices to us in conducting the research study.
Furthermore, we would like to express our appreciation to our families, friends and all the others for their assistance, support and encouragement for helping us to successfully complete our dissertation.
Last but not the least, we would like to thank our group members mutually in this research projects who are willing to work hard together to complete this project.
Thank you.
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The Impact of Derivatives on Firm Value
TABLE OF CONTENTS Page Copyright Page Declaration Acknowledgement Table of Contents List of Table List of Figures List of Appendices List of Abbreviations Preface Abstract CHAPTER 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 INTRODUCTION Introduction Background of the Study Derivatives in Malaysia Problem Statement Research Questions Research Objectives Chapter Layout 1-1 1-1 1-3 1-6 1-7 1-7 1-8 ii iii iv v ix x xi xii xv xvi
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CHAPTER
2 2.1 2.2 2.3
LITERATURE REVIEW Definition of Derivatives The Use of Derivatives to Hedge Risk Research Theory 2.3.1 Interest Rate Derivatives 2.3.2 Foreign Currency Derivatives 2.3.3 Commodity Derivatives 2-2 2-3 2-4 2-1 2-1
2.4
Empirical Discussion 2.4.1 Interest Rate Derivatives 2.4.2 Foreign Currency Derivatives 2.4.3 Commodity Derivatives 2.4.4 Firm Size 2.4.5 Leverage 2.4.6 Investment Growth 2.4.7 Dividend Per Share 2.4.8 Profitability 2-5 2-8 2-10 2-12 2-13 2-15 2-16 2-18
CHAPTER 3 3.1 3.2 3.3
RESEARCH METHODOLOGY Introduction Research Design Data Collection Method 3-1 3-1 3-1
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3.4
Variable Specification 3.4.1 Dependent Variable 3.4.2 Independent Variables 3.4.3 Control Variables 3-2 3-2 3-2
3.5
Data Analysis Technique 3.5.1 Tobin?s Q 3.5.2 Multivariate Analysis 3.5.3 White Heteroskedasticity-Consistent Standard Error and Covariance 3.5.4 Panel Data Techniques 3.5.5 Hausman Specification Test 3-7 3-8 3-10 3-4 3-5
3.6
Hypotheses Development 3.6.1 Interest Rate Derivatives 3.6.2 Foreign Currency Derivatives 3.6.3 Commodity Derivatives 3-11 3-12 3-13
CHAPTER
4 4.1 4.2 4.3 4.4
DATA ANALYSIS Descriptive Statistic Pearson Correlation Ordinary Least Square Result Pooled Data Analysis 4-1 4-7 4-7 4-12
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CHAPTER
5 5.1 5.2 5.3
CONCLUSION Conclusion Implications Limitations and Recommendations 5-1 5-2 5-3 R1 A1
References Appendices
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LIST OF TABLES
Table 1.1 4.1 4.2 4.3 4.4 4.5 4.6 4.7 The Different Types of Derivatives Traded at BMD Descriptive Statistic for Pooled Data Descriptive Statistic for 2007 Descriptive Statistic for 2008 Descriptive Statistic for 2009 Pooled Correlation Matrix Regression Results of the Factors That Affect Firm Value Pooled Data Analysis of Value Effects of Derivatives Use Decision 4.8 Hausman Specification Test
Page 1-5 4-3 4-4 4-5 4-6 4-10 4-11 4-15
4-16
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LIST OF FIGURES
Figure 3.1 Conceptual Framework
Page 3-7
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LIST OF APPENDICES
Appendix Appendix 1: Result of Pooled Effect Appendix 2: Result of Fixed Random Effect Appendix 3: Result of Random Effect
Page A-1 A-2 A-9
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LIST OF ABBREVIATIONS
ANOVA BMD CAPEX CEO CP CPO COMMEX DFFITS DPS ECM EPS EVA GMM GDP FCD FCPO FE FKB3 FKLI FMG3 FMG5 FPKO FTSE FUPO
Analysis of Variance Bursa Malaysia Derivatives Berhad Capital Expenditures Chief Executive Officer Commodity Price Crude Palm Oil Commodity and Monetary Exchange Difference between the Fitted Values Dividend per Share Random Effect Model Earning per Share Economic Value Added Generalized Method of Moments Gross Domestic Product Foreign Currency Derivatives Crude Palm Oil Futures Fixed Effect 3 Month Kuala Lumpur Interbank Offered Rate Futures FTSE Bursa Malaysia KKLCI Futures 3-Year Malaysian Government Securities Futures 5-Year Malaysian Government Securities Futures Crude Palm Kernel Oil Futures Financial Times and London Stock Exchange USD Crude Palm Oil Futures
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FX IR IRD JSE KLCE KLCI KLSE KLOFFE LR MDEX MME MVA MVE NPV OKLI OLS OSIRIS PE PS RE REIT R&D ROA ROE SGX
Foreign Exchange Interest Rate Interest Rate Derivatives Johannesburg Stock Exchange Kuala Lumpur Commodities Exchange Kuala Lumpur Composite Index Kuala Lumpur Stock Exchange Kuala Lumpur Options and Financial Futures Exchange Likelihood Ratio Malaysian Derivatives Exchange Malaysian Monetary Exchange Market Value Added Market Value Net Present Value FTSE Bursa Malaysia KLCI Options Ordinary Least Squares Online Search Information Retrieval Information Storage Pooled Effect Preferred Stock Random Effect Real Estate Investment Trust Research and Development Return on Asset Return on Equity Singapore Exchange
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SSFs SMEs TA TSE UK US USD
Single Stock Futures Small and Medium-sized Enterprise Total Assets Tehran Stock Exchange United Kingdom United State United State Dollar
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PREFACE
Derivative is the financial instrument in which the value is derived from an underlying asset such as interest rate, common stock, foreign exchange rate, commodity, etc. The use of derivatives by non-financial firms was sharply increasing over the past few decades. The purpose of using derivatives by a company is to hedge the risk they are facing in their daily business operations. For example, derivatives are used to hedge the interest rate risk because the fluctuation of interest rate may incur a higher cost of debt to the firm. Anyhow, do the firm hedging activities lead to enhance or improve the firm value? It has been an argument among many researchers in the past. Whether derivatives will increase the firm value is still on the debate. Therefore, we have conducted this research to discover whether it will increase the market value of a firm by using financial derivatives.
In this research, the total numbers of 300 Malaysian non-financial firms (based on their market capitalization) were selected, from the year 2007 to 2009. Tobin?s Q was used as a measurement of firm value; leverage, firm size, dividend per share, profitability and investment growth were control variables; interest rate derivative, foreign currency derivative and commodity derivatives were dummy variables. Pooled data technique was used in our research.
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ABSTRACT
Over the recent decade, firms increasingly using derivative to hedge their position. The empirical research on the valuation effect derivative has on firm value still remains debated. The purpose of our study is to investigate the effect of using derivative has on firm value in the Malaysia market by using a sample of top 300 non-financial firms in terms of market capitalization from the year 2007 to 2009. Secondary data and quantitative approach were used in our study. The required financial data were collected from companies? annual reports and OSIRIS database. To carry out the analysis, we used ordinary least squares (OLS) and panel data technique to estimate our model. The paper concluded that the usage of derivative could not improve the firm value. We found that commodity and currency derivative was not significantly related to the firm value. Interest rate derivative was partially significant to firm value; however, it was in a negative relationship.
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CHAPTER 1 INTRODUCTION
1.1
Introduction
This chapter provides the overall picture of the research project. It gives an introduction about the background of the research, followed by the problem statements, research questions and research objectives.
1.2
Background of the Study
Derivative is the security whose price is derived from an underlying asset. It serves as a contract between two or more parties on the trading of the underlying asset in the future point of time. In the derivatives market, the most common types of derivatives are future contracts, forward contracts, options and swaps. The main purpose of using derivatives by a firm is to hedge risk. Some may use to speculate and to earn an abnormal profit. According to Nguyen and Faff (2003), firms appeared to use interest rate derivatives to minimize the risk of financial distress. They found that firms used derivatives as a hedge rather than to speculate in the foreign exchange market.
Alkeback, Hagelin and Pramborg (2006) discovered that 59 percent of the non-financial firms in Sweden used derivatives in 2003 compared to 52 percent in 1996, which was a significant increase in derivatives usage among the SMEs. Besides that, the exchange exposure was the most the Swedish firms to manage with, compared to interest rate exposure. In 2003, almost every firm used derivative to manage their foreign exchange exposure and interest rate exposure.
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The Impact of Derivatives on Firm Value
Nguyen and Faff (2003) discovered that leverage and firm size were the two most important factors that induced a firm to make use of financial derivatives. However, Carter and Sinkey (1998) did not find the level of participation in the market for interest-rate derivatives was positively related to size. Other than that, El-Masry (2006) argued that larger firms were more likely to use derivatives than medium and smaller firms; public companies were more likely to use derivatives than private firms; and derivatives usage was greatest among international firms. Furthermore, Hentschel and Kothari (2001) examined that financial institutions hold slightly more interest rate derivatives compared with non-financial firms. Raturi (2005) suggested that derivatives were used by larger companies, especially in the life insurance industry.
On the other hand, except for the banks and financial firms, the use of derivatives by non-financial firms has grown rapidly in the last two decades. However, up to present, there is a little consensus regarding what is the effect of the use of derivatives on the market value of the firm (Bartram, Brown & Conrad, 2006). The Modigliani and Miller (1958) paradigm predict that the use of derivatives cannot add value if markets are perfect. However, modern finance theories indicate that there are certain circumstances under which a hedging program using derivatives can be a value enhancing.
Smith and Stulz (1985) argued that hedging could reduce the probability of a firm encountering financial distress by reducing the variance in firm value. For example, banks can use derivatives to reduce the probability of financial distress due to the uncertainty of the fluctuation in interest rate. However, from the finding of Carter and Sinkey (1998), community banks may reject to use derivatives because the cost of implementing a riskmanagement program was higher, such as the start-up costs like hiring trained personnel and development of the internal control systems.
Bartram et al. (2006) examined the effect of derivative use on firm risk and
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The Impact of Derivatives on Firm Value
value by using a large sample of non-financial firms from 47 countries. They found strong evidence that the use of financial derivatives could reduce both total risk and systematic risk, thus it led to a lower market beta and lower discount rate, therefore a higher firm value. Junior and Laham (2008) also found that the adoption of a hedging policy would increase the firm value.
Other than that, the use of derivatives would be influenced by managers because he was the one who responsible to diversify the risk relating to the firm. Smith and Stultz (1985) investigated that if managers? wealth was in aligning with the firm value, then it was optimal for them to completely hedge the value of the firm.
1.3
Derivatives in Malaysia
In the year of 1980, Malaysia set up the first derivative exchange which was known as Kuala Lumpur Commodities Exchange (KLCE). At the same year, KLCE introduced the first derivative product - Crude Palm Oil (CPO) future contract to the public and it was actively traded in KLCE. Up to present, CPO is still the main derivative product of KLCE, even though KLCE has introduced other commodity future contracts on rubber, tin, cocoa and etc. Although other commodity future contracts are less actively traded compared with CPO, but since they are good substitute contracts traded in foreign exchanges such as Tokyo, London and etc., therefore it would not be taken off from KLCE. Due to the reason that MME was unable to maintain the single contract by itself, it was forced to be merged with KLCE and became a new entity called COMMEX. 1
In addition, the Kuala Lumpur Options and Financial Futures Exchange (KLOFFE) was the first Malaysian financial derivatives exchange which
1
Bacha, O. I., & Merican, O. M. I. (2003). The market for financial derivatives: Removing impediments to growth, 4-5 1-3
The Impact of Derivatives on Firm Value
was established by a consortium of private companies in 1990. It launched the first product - Stock Index Future contract that based on a revamped Kuala Lumpur Composite Index (KLCI) in 1995. After five years later, KLOFFE introduced another product which was index option as its second product. For the KLCI options, it has a vary strike price in call and put option give to investors. However, in early 1999, the owner of KLOFFE sold the financial derivative exchange to the Kuala Lumpur Stock Exchange (KLSE) and become a KLSE?s wholly-owned subsidiary.2
In December 2000, KLOFFE and COMMEX merged together and became Malaysian Derivatives Exchange (MDEX). As a result of merging, MDEX was a single exchange that for all derivatives trading needs to consolidate into this exchange. Due to MDEX was a subsidiary that wholly owned by KLSE, therefore KLSE was a single exchange in Malaysia that provided the trading in stocks as well as both commodity and financial derivatives. After that, KLSE has changed its name to Bursa Malaysia Berhad, therefore MDEX became Bursa Malaysia Derivatives Berhad (BMD). 3
Since the entire derivatives are consolidated in BMD, therefore, now we have commodity, equity and financial derivatives that are ready to be traded in BMD. In total there are nine derivative contracts which are being traded in BMD by today. The nine derivatives contracts are stated at Table 1.1.
2
Deravatif in Malaysia, Retrieved March 06, 2011, from http://www.scribd.com/doc/8246440/deravatif-in-malaysia, 5-6. 3 Deravatif in Malaysia, Retrieved March 06, 2011, from http://www.scribd.com/doc/8246440/deravatif-in-malaysia, 6. 1-4
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Table 1.1: The Different Types of Derivatives Traded at BMD
Commodity Derivatives
Equity Derivatives
Financial Derivatives
Crude Palm Oil Futures FTSE Bursa Malaysia (FCPO) KLCI Futures (FKLI)
3 Month Kuala Lumpur Interbank Offered Rate Futures (FKB3)
USD Crude Palm Oil Futures (FUPO)
FTSE Bursa Malaysia KLCI Options (OKLI)
3-Year Malaysian Government Securities Futures (FMG3)
Crude Palm Kernel Oil Futures (FPKO)
Single Stock Futures (SSFs)
5-Year Malaysian Government Securities Futures (FMG5)
(Source: Bursa Malaysia, 2011)4
Among the equity derivatives, SSF is the most recent contract (introduced in 2006) that was added in. These futures are based on the individual stocks that listed on Bursa Malaysia and most of them are blue-chip stocks.5 Other than that, FUPO is a crude palm oil futures contract that is denominated in USD, whereas FCPO is denominated in Ringgit, both of them are treated as the worldwide pricing benchmark for palm oil. Bursa Malaysia has enlarged the offering in commodity derivatives that denominated on USD to globalize Malaysian futures market and Bursa Malaysia?s position. As a result, BMD has become the market that is internationally competitive on futures trading.6
4
Derivatives products, Retrieved March 12, 2011 from http://www.bursamalaysia.com/website/bm/derivatives/products/ 5 Single Stock Futures (SSFs), Retrieved March 12, 2011, from http://www.bursamalaysia.com/website/bm/products_and_services/derivative_resources/ downloads/faq_ssf.pdf, 1-2. 6 USD Crude Palm Oil Futures (FUPO), Retrieved March 12, 2011, from http://www.bursamalaysia.com/website/bm/derivatives/products/Commodity_Derivatives/ fupo2.html 1-5
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1.4
Problem Statement
Over the recent decade, firms increased to use derivative to hedge their position. The derivative market has experienced a rapid growth over the recent year. Even though information on firm derivative usages is widely available, the empirical research regarding whether the use of derivative will increase a firm value is still debatable.
Modigliani and Miller (1958) suggest that firm value will be independent of hedging if perfect capital markets exist (without transaction costs, taxes, bankruptcy cost, agency costs and information asymmetry). The main reason is because rational investors are assumed to diversify their portfolio themselves and therefore there is no value added for a firm to engage in hedging transaction. However, does derivative actually enhancing the firm value in reality? The empirical finding of whether used of derivative for hedging purposes has or has no impact on firm value is still mixed.
Many researchers have conducted empirical work on the impact of using derivative usage on firm value over recent decade. The result of the research is still mixed and therefore we cannot conclude whether hedging has significant impact on firm value. Jorion (1990) found that hedging on foreign currency has no impact on firm value. This result was inconsistent with the finding of Allayannis and Weston (2001). They found that the use of foreign currency derivatives would create value to the firm. Jin and Jorion (2006) investigated the U.S Oil and gas sector and they found an insignificant impact hedging has on firm value. Graham and Rogers (2001) found that hedging would create value to firm by enhancing their debt capacity. A similar research was conducted by Hagelin and Pramborg (2002) in Swedish firms and found that hedging would have a positive effect on firm value.
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The Impact of Derivatives on Firm Value
As a whole, the findings of empirical studies remain controversial; it is not clear whether the decision to use derivatives has an effect on firm valuation. Therefore, this paper extends the literature by testing the hypothesis of whether the use of derivatives is rewarded by a higher market value of a firm, using a sample of Malaysia?s firm.
1.5
Research Questions
This research is important to allow us to examine whether the use of derivatives affects the value of Malaysian non-financial firms. More specifically, we would like to investigate: 1. What is the effect of derivatives use on the firm value? 2. What type of derivatives will have significant impact on firm value? 3. Is the use of derivative can be served as an important indicator to measure the value of the firm?
1.6
Research Objectives
The main objective of this research is to investigate whether the derivatives are positively related to the firm value in Malaysia. As what we have stated in the problem statement, the effect of derivatives usage on firm value is still debatable because the results from various empirical researches show their own interpretation. Therefore this issue becomes our main purpose to conduct this research project. In order to have a deep understanding on the research, we specifically discuss the three main derivatives in the market which are interest rate derivatives, currency derivatives, and commodity derivatives. The objectives are specifically stated in the three forms show in the following.
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The first objective is to determine whether the interest rate derivative is positively related to firm value. Interest rate derivative is a form of derivative used to hedge the interest rate risk resulting from the fluctuation of interest rate, and thus affect the financial planning of a company. But how is the effectiveness of hedging interest rate by using the derivative?
The second objective is to find out whether the usage of currency derivative is positively related to firm value. For a multinational enterprise, they always deal with the foreign business partners. Because of this, they are facing the currency risk at all time and hence to use derivative to minimize the risk and losses. Therefore we want to discover if the usage of derivative can really help the firms to minimize the currency risk.
The third objective is to determine whether the use of commodity derivative is positively related to firms? market value. This type of derivative is always used by those companies or manufacturers to hedge the fluctuation of commodity price. For example, Airline industries buy the jetfuel forward contract to lock in the price of fuel at a certain rate in the future point of time.
1.7
Chapter Layout
The research paper consists of five chapters and is organized as follows:
Chapter 1 of this research project first illustrates the background of the research, then toward to explain the problem statements, and the objectives of this research which is going to be conducted. In Chapter 2, we conduct a literature review on the journals and use the findings and results given by these journals to support our research project. Chapter 3 discusses on the sample, key variables, and methodology used to examine the Malaysian firms? valuation reaction to the use of derivatives and. Besides that, we also develop the hypothesis and conceptual
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framework for this research project. Chapter 4 discusses about our findings, researched results and we conclude our research project in chapter 5.
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CHAPTER 2 LITERATURE REVIEW
2.1
Definition of Derivatives
From the definition of Chance and Brooks (2009), derivative is defined as the financial instruments whose returns are derived from those of other financial instruments. That is, their performance depends on how other financial instruments perform. Derivatives serve a valuable purpose in providing a means of managing financial risk. By using derivatives, companies and individuals can transfer, for a price, any undesired risk to other parties who either have risks that offset or want to assume that risk. There are different types of derivatives such as forward contract, future contract, swap, option, equity derivative, foreign exchange derivative, interest rate derivative and commodity derivative.
2.2
The Use of Derivatives to Hedge Risk
According to a survey from the International Swaps and Derivatives Association7, there were 94% of the world?s 500 largest companies in 2009 used the derivatives to manage and hedge their business and financial risks. The survey found that foreign exchange derivatives were the most widely used instruments which were 88 percent, followed by interest rate derivatives (83 percent) and commodity derivatives.
7
International swaps and derivatives association, News release April 12, 2009. Retrieved March 10, 2010, from http://www.isda.org/press/press042309der.pdf 2-1
The Impact of Derivatives on Firm Value
From the article of David Harper (2010)8, he mentioned the uses and the functions performed by derivatives are as follow: ? Foreign Exchange Risk: The risk that changes in the currency exchange rate will have an adverse effect on the company?s revenue. It also known as currency risk. ? Interest Rate Risk: Companies can hedge interest-rate risk in various ways. Consider a company wishes to sell a division in one year but the interest rate is expected to fall in the future, then it could purchase (or 'take a long position on') a Treasury futures contract to lock in the interest rate by today. Thus, the company is effectively locking in the future interest rate. ? Commodity or Product Input Hedge: This is the risk commonly faced by companies that are heavily sensitive to the price change of raw-material inputs or commodities. For example airline industry, it consumes lots of jet fuel. In the past, most airlines have given a great deal of consideration to hedging against crude-oil price increases.
2.3 Research Theory
2.3.1 Interest Rate Derivatives
Interest rate derivatives are instruments whose payoffs are dependent in some way on the level of interest rates. In the 1980s and 1990s, the volume of trading in interest rate derivatives in both the over-the-counter and exchange-traded markets increased very quickly. Many new products were developed to meet particular needs of end-users. The key challenges
8
Harper, D. (2010). How companies use derivatives to hedge risk. Retrieved March 10, 2010, from http://www.investopedia.com/articles/stocks/04/122204.asp 2-2
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for derivatives traders are to find good, robust procedures for pricing and hedging these products.9
There are different types of interest rate derivatives, one of these is interest rate cap. It can be characterized as a portfolio of put options on zero-coupon bonds with payoffs on the puts occurring at the time they are calculated. Analogously to an interest rate cap, an interest rate floor is a portfolio of put options on interest rates or a portfolio of call options on zero-coupon bonds.10
Swap options, are options on interest rate swaps and are another increasingly popular type of interest rate option. They give the holder the right to enter into a certain interest rate swap at a certain time in the future. Many large financial institutions that offer interest rate swap contracts to their corporate clients are also preparing to sell swap options to them or buy swap options from them. 11
2.3.2 Foreign Currency Derivatives
Firms in the plantation, industrial product, trading services, and consumer products manufacturing sectors are the main users of the foreign currency derivative (FCD) in Malaysia. It is a type of contract that derives the value from an underlying asset such as currency or exchange rate. Allayannis and Weston (2001) discovered that firm would have higher value by using currency derivatives in its risk management operation. In order to mitigate the impact of foreign exchange rate fluctuations, it has been claimed that firms could employ financial hedge strategies through foreign currency derivatives (Chiang & Lin, 2005). Since there are many investment tools
9
Hull, J.C. (2006). Options, Futures, and Other Derivatives, Seventh Edition. Pearson/Prentice Hall. Page 639 10 Hull, J.C. (2006). Options, Futures, and Other Derivatives, Seventh Edition. Pearson/Prentice Hall. Page 644 11 Hull, J.C. (2006). Options, Futures, and Other Derivatives, Seventh Edition. Pearson/Prentice Hall. Page 650 2-3
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are in high risk, in order to prevent unexpected losses in the future, investos tend to use foreign currency derivative to minimize the risk they are facing now such as foreign currency risk. Similar with the finding of Makar and Huffman (2008), they reported that US foreign-denominated debt issuers used foreign currency derivatives to hedge short-term risk effectively. Besides it also increased their firm value by not losing money on the premium paid out.
Bartram, Brown and Fehle (2006) found evidence that those firms have foreign currency transaction tend to use foreign currency derivatives. Foreign currency transaction normally comes with foreign currency risk. For the speculator, their motivation of using derivative is to earn an abnormal profit, so they intend to use FCD to speculate rather than to hedge, since this kind of derivative instrument is the marginal product that only needs minimum amount of initial capital and ends up to gain a huge profit. It is similar with the finding of Anand and Kaushik (2008) in which speculation was the objective of using foreign currency derivatives.
2.3.3 Commodity Derivatives
A commodity derivative is a derivative contact in which a commodity is the underlying asset. Commodity derivatives are the financial instruments that derive the value from the value of the underlying commodity in order to achieve price risk management (Lokare, 2007). It is necessary to understand the reason why commodity derivatives are important and also the role they can play in risk management. Because of the price of commodities, metals, shares and currencies fluctuate over time, the possibility of adverse price changes in the future creates risk for businesses. And hence derivatives are used by firms to reduce or eliminate price risk arising from unforeseen price changes (Ahuja, 2006).
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The Impact of Derivatives on Firm Value
Commodity derivatives are not new. In pre-Christian civilizations, forwards on agricultural products have already existed. Forwards are defined as contracts between two parties to deliver a certain product at an agreed price on the future certain date. On the other hand, futures are the standardized forwards that freely exchangeable on the market in which first appeared in Chicago in the 1840. Because the existence of exchanges that appeared to facilitate the matching of buyers and sellers of contracts, thereby lead to increase the liquidity of derivative markets. The historical role of commodity derivatives is that to hedge against inherent risks existing in commodity markets (Cinquegrana, 2008). The commodity derivatives trading in India has its long history. In today?s India, there are large numbers of agricultural commodity contracts are traded on the exchanges. The value of agricultural commodities traded as a proportion of overall GDP amounts to around 37 percent (70 percent of the agricultural GDP) in the country compared with the share of billion, oil and other metals is relatively low (Lokare, 2007).
2.4 Empirical Discussion
2.4.1 Interest Rate Derivatives
In the past few decades, the use of interest rate derivatives has grown substantially. Interest rate risk represents the most significant source of market risk for many lodging firms. Much of this exposure is from floatingrate bank loans because changes in interest rates can increase cash flow and earnings volatility in an uncertain interest rate environment. Higher interest rates can also make it more costly for firms to raise external financing. By matching the exposure of assets with the exposure of debt, managers can ensure that the supply of funds from operations and/or debt financing will match the demand for funds for its capital investment opportunities and reduce the need for costly external financing (Froot, Scharfstein & Stein, 1993). However, the recent research has questioned
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their importance and their efficacy in the risk management toolbox of nonfinancial firms. Guay and Kothari (2000) argued that the effect of derivative use was too small; whereas Faulkender (2005) showed that the firms in the chemicals industry tend to use interest rate derivatives to speculate rather than to hedge.
Singh (2009) conducted a research to investigate the relationship between the interest rate derivative positions, debt maturity structure, and exposure for a sample of lodging firms, gaming firms, and lodging REITs, for the period from 2000 to 2004. The results showed that lodging firms were positively exposed to interest rate risk. Interest rate derivatives such as interest rate swaps and caps were used in conjunction with debt maturity structure to mitigate interest rate exposure and to lower borrowing costs. By issuing floating debt and swapping into fixed-rate debt, smaller unrated firms would realize benefits from lower financing costs, lower costs of financial distress, and lower interest rate exposure. On the other hand, firms with high debt ratings were more likely to issue fixed-rate debt and swap into floating-rate debt. In addition, the results supported the conclusion that the yield spread has a positive and significant effect on swap usage.
Covitz and Sharpe (2005) discovered that smaller firms have more exposure on interest rate from their liabilities compare to the larger firms. Thus, smaller firm will tend to use the derivative to neutralize the interest rate exposures. For the larger firms, they will use their choice of debt structure to limit their interest rate exposures rather than with derivatives.
Batram et al. (2006) examined whether derivatives use was associated with higher firm value on a sample of 7263 non-financial firms from 48 countries. In order to test the relationship between derivatives use and firm-specific as well as country-specific factors, two types of models were estimated. The first was a single-equation PROBIT model using the full sample of general derivatives. The second was a trivariate PROBIT model
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The Impact of Derivatives on Firm Value
with separate equations for FX, IR, and CP derivatives. They found that only the firm that using interest rate derivatives has a positive valuation effect.
Nelson, Moffitt, and Graves (2005) examined with the samples of 5700 non-financial firms and their use of currency, interest rate, and commodity derivatives. Tobin?s Q as a proxy for firm value, they looked directly at the stock return performance of firms that disclosed the use of derivatives for the purpose of hedging. In the research they found that there was a negative effect of interest rate derivatives on firm value. Nguyen and Fatt (2007) addressed the question of whether the use of financial derivatives among a cross section of Australian firms delivered a positive increment in firm value. In doing so, they investigated both the relationship between an aggregate measure of derivatives and firm value as well as the impact that individual types of derivatives potentially have on firm market value, as proxied by Tobin?s Q. The result showed that there was a negative relationship between derivatives use and firm value. Rather, their result strongly indicated that the use of derivatives in general and the use of interest rate derivatives in particular lead to a reduction in firm value or a „derivative user? discount.
Ameer (2009) examined the state of risk management practices among Malaysian listed firms and evaluated the value-relevance of the notional amount of foreign-exchange (FCD) and interest-rate derivatives used by listed firms over the period 2003-2007. He applied the linear regression framework into his research and found that only a few firms hedge the market risks in Malaysia. The main users of the FCDs in Malaysia are the firm in the plantation, industrial product, trading services and consumer products manufacturing sectors. In addition, the total earning and the use of derivatives have a significant positive correlation. This findings showed that its contribution to a the valuation of firms was very minimal in Malaysia than other countries although there have a value-relevance by a disclosed notional amount of the derivatives
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The Impact of Derivatives on Firm Value
2.4.2 Foreign Currency Derivatives
Allayannis, Lel and Miller (2009) examined how corporate governance impacts firm value through hedging. They used foreign currency derivatives associated with a higher valuation for firms that have strong internal or external corporate governance. The data was collected from thirty-nine countries between 1990 and 1999 that were cross-listed in the U.S. as level II and level III ADRs, they split the country differences into internal (firm-level) as well as external (country-level) corporate
governance structures. The researcher used the market-to-book ratio as a proxy for Tobin?s Q to reflect a firm?s market value. They concluded that hedging premium only for firms that have strong internal and external corporate governance, while there was no hedging premium for firms with weak corporate governance. With strong internal and external, foreign currency derivatives added value to the market firm value or vice versa.
Allayannis and Weston (2001) investigated the impact of using foreign currency derivative has on the firm value. They used 720 largest U.S. nonfinancial firms between 1990 and 1995 as a sample and used Tobin?s Q as an approximation for firm?s market value and robustness tests. They also measured the market-to-book ratio (simple Q) and the market-to-sales ratio. Their results concluded that foreign currency derivative was positively and significantly correlated with the firm value. The researcher also found that the firm value would be increased and if they performed hedging activities and vice versa.
Nguyen and Faff (2003) reexamined on an empirical exploration of the motives behind the aggregate use of financial derivatives- foreign currency and interest rate derivatives by Australian companies. This journal data contained sample of non-financial Australian companies- 469 firms from 1999 and 2000 from the Connect database. Logit and Tobit regression and also the LR (likelihood ratio) statistic tests were used to analyze the result. The result showed that foreign currency derivative appeared to be cost2-8
The Impact of Derivatives on Firm Value
based and related to the issuance of foreign-currency-denominated debt. The use of FCD was strongly linked to value-enhancing motives.
Capstaff, Marshall and Hutton (2007) investigated the use of FCD by French firms before and after the introduction of the euro. The purpose was to examine if the introduction of euro currency on financial practices would actually reduced the currency risk, and hence reduced the motive of using foreign currency derivative to hedge the risk. Samples of 120 French firms were collected across the periods before and after the introduction of the euro 1996 and 2000. Various types of method were used to test the result, such as F-statistic, Jarque–Bera (J–B), Ryan Joiner statistics, the White?s test, Berry and Feldman graphical technique and also DFFITS test. As a result, after the adoption of the euro, the level of exposure to foreign currency risk decreased, hence lead to a decrease in the level of foreign currency derivative usage.
Allayannis and Ofek (1997) examined the purpose of using foreign currency derivatives. The total of 500 non-financial firms was selected as the sample. The researcher found that there was a strong negative association between foreign currency derivative use and firm exchangerate exposure, the meaning is that firms used derivatives to hedge rather than to speculate in the foreign exchange markets. A firm's exposure to exchange-rate movements was mitigated through the use of foreign currency derivatives.
Makar and Huffman (2008) examined the relationship between UK multinationals? stock returns and changes in the principal exchange rate. They also investigated whether the firms effectively used foreign currency derivatives and foreign-denominated debt to lower the currency risk associated with the bilateral exchange rate to which they were more likely to expose with. The sample consisted of 44 firms UK multinationals listed in the June 2001 FTSE 250 that operated in the non-financial sector, for the 1999–2002 sample periods. They used OLS Regression, the Shapiro –
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The Impact of Derivatives on Firm Value
Wilk test for non-normality, and the White test for heteroskedasticity and also hypothesis tests. The result indicated that the currency risk could be effectively hedged by the financial currency-hedge techniques.
Hentschel and Kothari (2001) conducted a research to investigate whether the use of derivatives allowed firms to reduce their level of riskiness. A total number of 325 non-financial firms and 100 financial firms were selected as the sample. They used Tobin?s Q, univariate test and multivariate test to test their result. Their result indicated that there was no significant relationship between the volatility of a firm?s stock prices and the size of the firm?s derivatives position.
Magee (2009) investigated the effect of foreign currency hedging with derivatives on firm value in a dynamic panel framework by using the system generalized method of moments (GMM) estimator. By using the system GMM estimator, it allows the researcher to control for unobserved firm specific factors, persistence in firm value and feedback from the past amounts of firm value to the current amount of foreign currency hedging. The sample consisted of 408 large U.S. non-financial firms with foreign sales from operation abroad during the period of 1996 to 2000 which was measured by Tobin?s Q. The result showed that the foreign currency hedging would increase firm value when foreign currency hedging was assumed to be strictly exogenous. However, the researcher also found that the use of foreign currency derivatives no longer affect the firm value.
2.4.3 Commodity Derivatives
Commodity derivatives markets have witnessed tremendous growth in recent years. Chang, Hong and Kuan (2005) examined the impact of hedging activities of Canadian oil and gas companies on their stock return and firm value for the period of 2000-2002. The impact of hedging on firm value was measured by Tobin's Q ratio by using both linear and nonlinear
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The Impact of Derivatives on Firm Value
models. They found that the large Canadian oil and gas firms were able to hedge against the downside risk induced by unfavorable oil and gas price changes. However, gas hedging appeared to be more effective than oil hedging when downside risk presented. Therefore, hedging for gas (together with profitability, leverage and reserves) has a significant impact on firm value. Bartram et al. (2006) did a survey on the effect of derivative use on firms? risk measures and value. The derivative use was more prevalent in firms with higher exposures to interest rate risk, exchange rate risk and commodity prices. They did the research by using a large sample of 6,888 non-financial firms from 47 countries. They found strong evidence that the use of financial derivatives reduced both total risk and systematic risk and there was a positive relationship of derivative use on firm value but the effect was not strong.
Carter, Rogers and Simkins (2002) examined a sample of firms in which hedging positions could achieve economically significant objectives. They investigated jet fuel hedging behavior of firms in US airline industry during 1994-2000 to examine whether such hedging is a source of value for these companies. The result showed that jet fuel hedging was positively related to airline future purchases of jet fuel. They found evidence to support view that airlines, on average, increased firm value by using derivatives to hedge against changes in jet fuel prices.
However, Jin and Jorion (2006) examined the hedging activities of a sample of 119 U.S. oil and gas produce from 1998 to 2001 with the measurement of Q ratios, it showed that hedging did not affect the market value and there was no difference in firm values between firms that hedged and firms that did not hedge.
From the research of Hentschel and Kothari (2001) using data from ?nancial statements of 425 large U.S. corporations, they investigated
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The Impact of Derivatives on Firm Value
whether ?rms systematically reduce or increase their riskiness with derivatives. They found that many of the largest U.S. corporations were active participants in derivatives markets and manage their exposures with large derivatives positions. Firms with derivatives hold similar notional principals of foreign exchange and interest rate derivatives but they hold almost no commodity derivatives. Non-?nancial ?rms hold slightly more foreign exchange derivatives, while ?nancial institutions hold slightly more interest rate derivatives. In the research, they found out that there was no association between the volatility of a ?rm?s stock prices and the size of the ?rm?s derivatives position. Moreover, a ?rm?s exposures to variations in interest and exchange rates were not directly related to the ?rm?s derivatives position.
Nelson et al. (2005) examined the annual stock performance of 1,308 U.S. firms over the period per year 1995-1999. They found that firms that hedged outperform other securities by 4.3 percent per year on average. They pointed out that the over performance was entirely due to larger firms that hedged currency. However, they discovered that there were no abnormal returns for firms to hedge either with interest rate or commodity derivatives.
2.4.4 Firm Size
Cohen, Levin, and Mowery (1987) found that there was no significant relationship between size and R & D intensity once care is taken to separate the influence of business unit and firm size. Therefore, we might have to take into account any other factors to get accurate point.
Mak and Kusnadi (2005) examined the impact of corporate governance mechanisms on the firm value of Singapore and Malaysia firms. The sample included 271 firms listed on the SGX and 279 firms listed on the KLSE, financial data, board composition, ownership structure, and other
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The Impact of Derivatives on Firm Value
relevant data for each firm for the 1999 or 2000 financial years. They used Tobin?s Q and multivariate tests as measurement. The result showed that there was an inverse relationship between board size and firm value in both countries.
Ushijima (2003) investigated the evaluation of corporate multinational and its effect on the stock market valuation of the firm. The sample was balanced panel of manufacturing firm continually listed on Tokyo Stock Exchange from 1985 to 1995, total of 5124 firm-year observations. This project was measured by simple proxy of Tobin?s Q. The result showed that firm size which was a central screw to the multinational company and multiplier value for the company was not value negative with itself, in fact the value of multinational firm increase with its firm size, which presumably, monitoring problem would be worse, could not be recovered by theory.
2.4.5 Leverage
Before a firm undertakes a project, it must have sufficient funds with itself. Normally, a big firm will borrow loan from bank or issue bond to raise funds, then it only can increase their potential returns. However, at the same time the companies? debt will increase as well. Leverage is calculated by the amount of debt that uses to finance firm?s assets. Firms that have more debts than assets are considered as high leverage firm. Investor usually will advert to the high leverage firms because there are high possibilities that the firm may not be able to repay the debt. According to Ward and Price (2006), financial leverage was the proportion of capital, the greater the level of debt, the higher the leverage. According to Modigliani and Miller?s (1958), return on equity should be increased if the firm?s level of debt increases. Besides, Ward and Price (2006) indicated that if there was an increase in debt-equity ratio,
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The Impact of Derivatives on Firm Value
shareholder returns would raise. However, Rajan and Zingales (1995) argued that there was a negative relationship between debt and profitability.
Iturriaga and Crisostomo (2010) examined the effect of leverage, dividend payout, and ownership concentration on firm value with or without growth opportunities. A total of 213 samples from Brazilian firms were collected between 1995 and 2004. They used Generalized Method of Moments (GMM), Hansen Test and Arellano-Bond to test the results. The result showed that leverage has a dual effect on the value of the firm, which was negative for firms with growth opportunities and positive for firms without growth opportunities. Rayan (2008) examined whether the firms? financi al leverage was positively or negatively related to firm value in a South African context. The data that they used in their research was secondary data, which was sourced from Mcgregor BFA database for the period 1998-2007. 113 Johannesburg Stock Exchange (JSE) listed firm were included, which were stratified by industry. The method used was regression analysis. The result showed that there was a negative relationship between firm value and firms leverage.
Salehi and Biglar (2009) examined whether the capital structure decision would have an impact on firms? performance. They applied the data of 117 corporate in Tehran Stock Exchange (TSE) in a 5-year time horizon (20022007). Descriptive statistics containing mean, standard deviation and inferential statistics containing Pearson Correlation, and ANOVA test were used in their research. The result showed that firm value was negatively related to the firm?s financial leverage.
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The Impact of Derivatives on Firm Value
2.4.6 Investment Growth Previous literatures have tried to examine the impact of the firm?s long term capital expenditure or spending decision on its market value. Fama and Jensen (1985) stated that during the efficient market, if the managers decide to choose the investment project with positive NPV value, the firm value and shareholders wealth thus can be maximized and market reaction should be positively for any announcement of a new investment decisions by a firm.
Ehie and Kingsley (2010) investigated the relationship between the investments in R&D and market value among the firms by using a sample of 26,499 US firms over the period of 1990 to 2007. After they controlled the firm and market-related factors, they found out that R&D expenditures gave persistent positive effect on market value for both manufacturing and service firms.
Bajo,
Bigelli
and
Sandri
(1998)
studied
the
new
investment
announcements by Italian firms listed on the Milan Stock Exchange in a period of 1989-1995. They found that there was a positive relationship between stock price and new investment decisions. In additions, stock price responded better for joint venture announcements and for non-state owned companies.
Chung, Wright and Charoenwong (1998) examined the effect of corporate capital expenditure decisions on share prices. They collected the data on capital expenditure announcements from US companies using Nexis/Lexis services over the 15 year period (1981-1995). By using the certain sample selection criteria, they gathered 308 capital expenditure announcements and computed the Tobin?s Q for each compa ny, and then they separated the company into high Tobin?s Q group and low Tobin?s Q group. According to previous studies, firms with high Tobin?s Q ratio were expected to have positive NPV projects and vice versa, thus increased in
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The Impact of Derivatives on Firm Value
capital expenditures of those firm were expected to be positively accepted by the market and hence increased in share price and vice versa. However, the firms with low Tobin?s Q ratios were perceived as having a lack of valuable or low profitable investment opportunities. Market reactions generally were less positive toward the announcements of capital expenditure increase, but tend to view favorably if it reduced capital expenditures. They discovered that market did respond strongly to good decisions when there was an increase of capital expenditures by the firms with high Tobin?s Q and vice versa. However, the decision to decrease (increase) the capital spending by the firms with high Tobin?s Q (low?s Q firm) did not have significant negative impact on market reactions. They concluded that firm?s growth prospects determined the market?s reaction to their capital expenditure decisions.
2.4.7 Dividend Per Share
Miller and Modigliani's (1961) irrelevance theorems proposed that relationship between dividend policy and firm?s val ue is independent under certain assumptions such as perfect capital market and in the absence of taxes, bankruptcy costs, and asymmetric information. The distribution of cash dividend to shareholders was believed that should not have any impact on a firm?s stock prices. Lastly, the Miller an d Modigliani concluded that firm?s value could only be affected by firm?s investment policy alone which generated future cash flow based on the investment undertaken and not influenced by the manner in which its cash flows were split between dividend and retained earnings. “Dividend signaling hypothesis” was initially mentioned in Lintner (1956) paper, and further enhanced by Fama, Fisher, Jensen, and Roll (1969) and Ambarish, John, and Williams (1987). They believed that manager could distribute dividend to signal asymmetric information about the firm?s
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The Impact of Derivatives on Firm Value
future growth prospects, because manager was believed to have reliable private information about the firm future financial position and could signal those private information to investor through dividend distributions. Market generally believed that dividend change announcement would convey valuable information regarding the firm future growth prospects and earnings. Therefore, an announcement of a dividend increasing or decreasing was followed by an increase or decrease of stock prices subsequently.
Lang and Litzenberger (1989) suggested that free cash flow hypothesis explaining stock price reaction to dividend change announcements. Significant stock price behavior (increase in stock price) could occur when investors expected that the increase of dividend could limit the cash flow available for the firm?s managers to invest in the negative NPV or wasteful projects, whereas investors expected that announcements of decrease of dividend may signal that firm?s overinvesting policy and thus decrease of stock prices subsequently.
Azhagaiah and Priya (2008) examined the relationship between the shareholders? wealth and dividend policy on Organic and Inorganic Chemical Companies in India over the period of 1997 to 2006. During that period, any companies paid dividend for 3 years or more were treated as dividend paying company, otherwise was served as a non-paying company. The result indicated that there was a significant difference in average market value relative to book value of equity between dividend companies and non-dividend companies of both organic and inorganic chemical companies. They concluded that generally higher dividend did increase the market value of the firm and vice versa.
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2.4.8 Profitability Modigliani and Miller (1958) stated that a firm?s value could be maximized by using more debt in its capital structure; debt would help the firm to decrease their average cost of capital and enhance profitability as long as its ROA was greater than the before-tax interest paid on debt. ROE was found to be insignificant in determining the firm value.
Hall and Brummer (1999) determined which internal performance measures of a company correlate the best with its external performance measures as represented by the Market value added (MVA) of the corporation. MVA is the external method that used to determine the wealth of shareholder while for the internal measures of shareholder value creation is Economic value added (EVA) and other variable or ratios. As a result, they found out that there was a positive correlation coefficient between MVA and discounted EVA when inflation adjustments to the data had been made. Besides, there were slightly lower positive correlations were obtained between MVA and more traditional accounting-based corporate performance measures such as return on assets (ROA), return on equity (ROE), earnings per share (EPS) and dividends per share (DPS).
Mir and Nishat (2004) examined the link between corporate governance structure and the firm performance in Pakistan by using weighted least square regression techniques. The sample consisted of 248 firms randomly selected from the listed companies during 2003. The parameters of corporate governance were related to management, shareholders or stakeholders and board of directors, etc. While return on asset (ROA), Tobin?s Q and stock return were included in performance parameter. The result showed that there was positive impact on firm performance by corporate governance structure variables such as percentage block holding by individuals and family members and by industrial companies. However, the percentage of block holding by insider has negative signal
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The Impact of Derivatives on Firm Value
on firm performance. If CEO acts as chairperson of board of directors, the firm performance will be affected negatively. There was no impact on firm performance shown by the composition of board. Furthermore, the firm size has a positive impact on the performance of firm but the expected leverage has a negative relationship with performance.
Ukenna, Ijeoma, Anionwu, and Olise (2010) studied on the relationship between the human capital in a company and the firm?s performance. Their research objective was to find out to what extend the investment on human capital of a company will impact on its overall performance. Second, they wished to discover the perception of a small company regarding to the relationship between human capitals investment and the firm?s performance. They used a sample of twenty five small scale business in Nigeria with the criteria of the amount of staff was less than six and its capital base was not more than hundred thousand naira. The business owners were drawn from bookshops, supermarkets, business centers, computer schools, and sellers of computer accessories. The result showed that there was a strong relationship between the human capital effectiveness and financial performance of a small scale firm.
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The Impact of Derivatives on Firm Value
CHAPTER 3 RESEARCH METHODOLOGY
3.1
Introduction
This chapter outlined the research design, described the sample population and sampling procedures and methods used for data collection. The variables and formulas used in this study were shown and the data analysis technique used will be explained.
3.2
Research Design
The study was aimed at examining the valuation effect of derivatives used in Malaysia market using a sample of 300 non-financial firms over the period 2007-2009. The research adopted quantitative approach and secondary data were used for this study. The approach taken was the application of linear regression framework and panel data technique.
3.3
Data Collection Method
Sample companies were selected based on their market capitalization. The sample in this study comprised the top 300 non-financial firms in terms of market capitalization. The required financial data were collected from OSIRIS database and annual reports of companies over the years 2007-2009. Firms were classified as derivative user or non-user of derivatives based on a search from their annual reports for information about the use of derivatives. We used a dummy variable that was set to one for firms that use any types of derivatives and zero for non-user firms.
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The Impact of Derivatives on Firm Value
The aggregate use of financial derivative was separated into three subsets which are foreign currency derivative, interest rate derivative and commodity derivative. Dummy variable was assigned to each type of derivatives.
3.4
3.4.1
Variables Specification
Dependent Variable
Market values of the firm will be the dependent variable and it was proxy by Tobin?s Q. We adopted the formula approximate q developed by Chung and Pruitt (1994); where the approximate q was calculated by using market value of firm value plus preferred share plus debt and then divided by book value of the total assets; where debt was the value of the firm?s short-term liabilities minus short-assets plus book value of the firm?s long term debt.
3.4.2 Independent Variables
There are three independent variables which included foreign currency derivatives, interest rate derivatives and commodity derivatives. We assigned a dummy variable that was set to zero for firms that do not use derivatives and one for firm that use derivatives.
3.4.3 Control Variables
We included the following control variables, as in Allayannis and Weston (2001). The set of control variables in Tobin?s Q regression included factors known to explain the cross-section of firm value. These factors included:
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The Impact of Derivatives on Firm Value
i.
Size. The logarithm of total assets was used to control for firm size. Even though the relationship between firm value and firm size remained mixed, but we controlled the firm size for two reasons. According to Allayannis and Weston (2001), they found differences in Tobin?s Q for small firm compared to larger firm where small firms were associated with higher Tobin?s Q. But, on t he other hand, Bodnar, Marston and Hayt (1998) 12 found that large firms were more likely to hedge than small firms.
ii.
Leverage. Leverage was proxy by the ratio of long-term debt to the market value of firm. According to Fama and French (1998) and Allayannis and Weston (2001), they found a negative relationship between leverage and firm value.
iii.
Profitability. Profitability was considered as a key value driver. We used the return on assets and return on equity to control for profitability.
iv.
Investment growth. Investment opportunity is proxy by CAPEX (the ratio of capital expenditures to market value of firm). According to Myers (1976), future investment opportunities will have an impact on firm value. Hedgers may have larger investment opportunities, thus it is important to control the variable.
v.
Dividend per share. We controlled for dividends by using dividend per share rather than dummy variable. According to the study conducted by Fama and French (1998), they found that dividends announcement will convey information about future profitability.
Finally we excluded the variables, industrial and geographic diversification, that appeared in Allayannis and Weston (2001).
12
Bodnar, G. M., Marston, R. C., & Hayt, G. (1998). 1998 Survey of financial risk management by U.S. non-financial firms. Wharton/CIBC World Markets 1998 Financial Risk Management Survey: Executive Summary. 3-3
The Impact of Derivatives on Firm Value
3.5
Data Analysis Technique
3.5.1 Tobin’s Q The firm?s market value was calculated by using the formula of approximate q (Chung and Pruitt, 1994) 13 . We adopted the formula approximate q developed by Chung and Pruitt (1994), as the
measurement of the firm market value in our research. They created a simple formula to approximate the Tobin?s q of Lindenberg and Ross (1981)14 where the formula involved relatively easy calculation compared to the L-R?s Tobin?s q and required only basic accounting data that can be easily collected from financial statement of the firms. A very high correlation between the Lindenberg-Ross?s Tobin?s q and approximate q have been observed. They found that at least 96.6 percent of the variability of Tobin?s q was explained by approximate q. The primary difference between L-R and approximate Tobin?s q is that the latter assumed that the replacement values of a firm?s plant, equipment and inventories equal to their book value. The formula was defined as:
Approximate q= (MVE+PS+DEBT)/TA MVE = product of a firm?s share price and the number of common stock shares outstanding PS = liquidating value of the firm?s outstanding preferred stock DEBT = short-term liabilities - short-term assets + book value of long term debt TA = book value of the total assets of the firm
In using the formula to calculate q value, we might get a negative value. Some of the firms did not use long term debt to finance their business and
13
Chung, K. H. & Pruitt., S. W. (1994). A simple approximation of Tobin?s q, financial management, 23(3),70-74 14 Lindenberg, E. B., & Ross, S. A. (1981). Tobin?s q ratio and industrial organization. Journal of Business, 1-32 3-4
The Impact of Derivatives on Firm Value
they have more short term assets than short term liabilities; this has resulted in a negative debt value. When this negative debt value is too big and overweighs the market value of firm and preferred shares, the q value will turn out to be a negative value.
3.5.2 Multivariate Analysis
From the empirical research of Khediri (2010), he developed the multivariate analysis and estimated a specification for the regression models to investigate whether derivatives use are valued at a premium. He estimated the following equations: Tobin?s Qit = ? + ? (derivatives use decision) + ?? j (control variable j) + µi + ?it Where: Tobin?s Q = Market value of the firm and measure how much v alue is created for given amount of assets. Derivatives = Dummy variable equal to 1 for firm using derivatives, otherwise 0 Derivatives use extent = Firm?s outstanding notional amount of derivatives scaled by firm size ? = Constant ? = Estimated coefficient for corporate hedging proxies. ? = Estimated coefficient for control variables. µi = Individual effect of firm. ?it = Error term.
Since our research objectives are similar with that objectives founded in Khediri?s research, thus we adopted the formula used by Khediri?s .
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The Impact of Derivatives on Firm Value
Our multivariate analysis is as below: Tobin?s Q = ?1 + ?2 DUMINT + ?3 DUMCOM + ?4 DUMCUR + ?5 SIZE + ?6 LEV + ?7 ROA + ?8 ROE + ?9 INVG + ?10 DPS ?1 ?2 DUMINT
= Constant = 1 if firm using interest rate derivative and 0 otherwise
?3 DUMCOM ?4 DUMCUR ?5 SIZE ?6 LEV
= 1 if firm using commodity derivative and 0 otherwise = 1 if firm using currency derivative and 0 otherwise = Log of total assets = Leverage; calculated by total debt divided by total equity = Return on asset; calculated by net income divided by total assets = Return on equity; calculated by net income divided by shareholders? equities = Investment growth; calculated by capital expenditure divided by market value of firm = Dividend per share
?7 ROA ?8 ROE ?9 INVG ?10 DPS
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The Impact of Derivatives on Firm Value
Figure 3.1: Conceptual Framework
Interest Rate Derivatives
Foreign Currency Derivatives
Commodity Derivatives
Size
Leverage
Firm Value
Profitability
Investment Growth
Dividends per share
3.5.3
White
Heteroskedasticity-Consistent
Standard
Error
and
Covariance
Heteroskedasticity-consistent standard errors and covariance has been used to deal with the problem of heteroskedasticity by producing more normally-distributed standard errors.
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The Impact of Derivatives on Firm Value
3.5.4 Panel Data Techniques
Panel data, also called longitudinal data or cross sectional time series data, are data where multiple cases were observed at two or more time periods. In this study, panel data technique is used and different empirical models are considered. Most other studies assume is used and different empirical models are considered. Most other studies assume that the unobservable individual effect is zero and use a pooling regression to estimate the Tobin?s Q equation. The assumption of zero unobservable individual effect is too strong that there is large heterogeneity across firms. To control for individual firms heterogeneity, we employ a random effect as well as fixed effect model.
-FIXED EFFECT MODEL
Fixed effects model is the model to use when you want to control for omitted variables that differ between cases but are constant over time. It lets you use the changes in the variables over time to estimate the effects of the independent variables on your dependent variable, and is the main technique used for analysis of panel data. There are five assumptions under this model: i. Assumed that intercept and slopes are the same over time and individuals and the error term captures over time and individuals. ii. Assumed the slope coefficients are constant but the intercept varies over individuals. iii. Assumed the slope coefficients are constant but the intercept varies over individual and time. iv. v. Assumed that all coefficients vary over individuals. Assumed the intercept and coefficients vary over individual and time.
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The Impact of Derivatives on Firm Value
The model is adequate if we want to draw inferences only about the examined individuals. Yi,t = ?i + xi,t? + ei,t Yi,t = dependent variable ?i = unobserved random variable characterizing each unit of observation xi,t = vector of observable random variables ? = vector of parameter of interest
ei,t = stochastic error uncorrelated with x
-RANDOM EFFECT MODEL
The random effect model is the model to use when there are some omitted variables may be constant over time but vary between cases, or there are some omitted variables that may be fixed between cases but vary over time.
The key assumption under this model is there are unique, time constant attributes of individuals that are the results of random variation and do not correlate with the individual regressors. This model is adequate, if we want to draw inferences about the whole population, not only the examined sample. If the cross section data are “drawn” from a large population, they may not act in a similar way with respect to the independent variable.
Start with basic model
Yit ? ?1i ? ? 2 X 2it ? ? 3 X 3it ? uit
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The Impact of Derivatives on Firm Value
Instead of treating ? 1 as fixed, we assume that it is a random variable with a mean value of ? 1 , and the intercept value for an individual company can be expressed as
?1i ? ?1 ? ?i
Where of
i ?1 ,2,...,50
?i
is a random error term with a mean value of zero and variance
? e2
Yit ? ?1 ? ? 2 X 2it ? ?3 X 3it ? ? i ? uit
Yit ? ?1 ? ? 2 X 2it ? ? 3 X 3it ? wit
The composite error term wit consists of two components,
?i which is the
cross section, or individual-specific, error component, and u it , which and is the combined times series and cross section error component. In ECM (random effect model), the intercept ? 1 represents the mean value of the entire cross sectional intercepts and the error component
?i
represents the (random) deviation of individual intercept from this mean value.
3.5.5 Hausman Specification Test
Hausman
specification
test
(Hausman,
1978)
was conducted
to
statistically test which empirical model is most suitable for estimating Tobin?s Q equation. The test evaluated the significance of an estimator versus an alternative estimator. It helped one evaluate if a statistical model corresponds to the data.
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The Impact of Derivatives on Firm Value
3.6
3.6.1
Hypotheses Development
Interest Rate Derivatives
Singh (2009) found that lodging firms were positively exposed to interest rate risk. According to him, smaller unrated firms tend to benefits from lower cost of financing, financial distress and interest rate exposure if a firm issue floating debt and swapping into fixed-rate debt. By contrast, firms with high debt ratings were more likely to issue fixed-rate debt and swap into floating-rate debt. In short, the results supported the conclusion that the yield spread has a positive and significant effect on swap usage. In addition, Batram et al. (2006) also discovered that only the firm that using interest rate derivatives had a positive valuation effect. Moreover, Covitz and Sharpe (2005) investigated that smaller firms have more exposure on interest rate from their liabilities compared to the larger firms. Therefore, smaller firms tend to use derivative to neutralize their interest rate exposures whereas, larger firms will use their choice of debt structure to limit the interest rate exposures rather than with derivatives.
However, the authors examined non-financial firms with their use of commodity derivatives, currency and interest rate, and their finding showed a negative impact of interest rate derivatives on firm value (Nelson et al., 2005). Besides, Nguyen and Fatt (2007) also found that there was an adverse relationship between firm value and derivatives use. They investigated both the relationship between firm value and aggregate measure of derivatives as well as the impact that individual types of derivatives potentially have on firm market value. Their result strongly indicated that the use of interest rate derivatives in particular and the use of derivatives in general lead to a reduction in firm value or a „derivative user? discount.
As a result, different authors came out with different result regarding to the issue of whether the interest rate derivative can affect firm value. Some
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The Impact of Derivatives on Firm Value
authors found that there was a positive effect of interest rate derivatives on firm value and vice versa. Therefore, the hypothesis was proposed as:
H1: Interest rate derivative is positively related to firm value
3.6.2 Foreign Currency Derivatives
Firms in the plantation, industrial product, trading services, and consumer products manufacturing sectors are the main users of the FCDs in Malaysia. From the research of Hentschel and Kothari (2000), they found there was no significant relationship between the volatility of a firm?s stock price and the size of the firm?s derivative position. Besides that, Mag ee (2009) suggested the foreign currency hedging has no impact on firm value after controlling for the dependence of foreign currency hedging on past amounts of firm.
Bartram et al. (2006) studied on the purpose of using derivatives by a firm. The firms with foreign currency transactions tend to use foreign currency derivatives, this is because foreign currency transaction normally comes with foreign currency risk. Once the risk has been hedged, shareholder wealth maximization will be achieved, therefore firm value will increase. From the findings of Allayannis and Weston (1998), there was evidence that the use of currency derivative was in a positive association with the firm value. Besides that, Makar and Huffman (2008) found US foreigndenominated debt issuers could hedge short-term risk effectively by using foreign currency derivatives. Thus, we develop our research hypothesis as:
H1: Currency derivative is positively related to firm value
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The Impact of Derivatives on Firm Value
3.6.3 Commodity Derivatives
From the research of Chang et al. (2005), they found that hedging activities in an operation has a significant impact on firm value. They conducted a study on the impact of hedging activities of Canadian oil and gas companies on their stock return and firm value for the period of 20002002. The impact of hedging on firm value was measured by Tobin's Q ratio by using both linear and nonlinear models. The result indicated that in particular hedging for gas, together with profitability, leverage and reserves has a significant impact on firm value.
Besides that, Bartram et al. (2006) also agreed that the use of commodity derivative will improve the firm value. They conducted a survey on the effect of derivative use on firms? risk measures and value by using a large sample of 6,888 non-financial firms from 47 countries. They found strong evidence that the use of financial derivatives reduced both total risk and systematic risk and there was a positive relationship of derivative used on firm value but not strong.
Another research from Carter et al. (2002) investigated jet fuel hedging behavior of firms in US airline industry during 1994-2000 to examine whether such hedging was a source of value for these companies. The result showed that they found evidence to support the view that airlines, on average, increased firm value by using derivatives to hedge against changes in jet fuel prices.
However, Jin and Jorion (2006) found that there was no difference in firm values between firms that hedge and firms that do not hedge. They used the sample of 119 U.S. oil and gas produce from 1998 to 2001 with the measurement of Q ratios.
Nelson et al. (2005) examined the annual stock performance of 1,308 U.S. firms over the period per year 1995-1999. They found that firms that hedge
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The Impact of Derivatives on Firm Value
outperformed other securities by 4.3 percent per year on average. However, they found no abnormal returns for firms hedging either interest rates or commodities. From all the researchers? works stated as above, they have found a different answer about the issue of whether the firm value will be improved if the firm undergoing hedging activities. In common sense, if a firm was using derivative to hedge the firm?s risk in a correct manner, theoretically it will reduce the firm?s risk overall, then it should lead to firm value improvement. Thus, we developed the hypothesis as:
H1: The commodity derivative is positively related to firm value
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The Impact of Derivatives on Firm Value
CHAPTER 4 DATA ANALYSIS
4.1
Descriptive Statistic
Table 4.1 to 4.4 provide a summary of the descriptive statistic of dependent variable (Tobin?s Q) and i ndependent variables (interest rate derivative, commodity derivative, currency derivative, ROA, ROE, firm size, leverage, investment growth and dividend per share) from year 2007 to 2009 and panel data which includes all the three years. The mean, median, maximum, and minimum of each variable are shown in the tables.
From the result of descriptive statistic of pooled data shown in Table 4.1, it showed that the mean (medium) of Tobin?s Q was 0.8634 (0.5576). This indicated that the firm market value was less than the recorded value of the assets of the company, in other words Malaysia listed companies have been undervalued by the market. The profitability ratios (ROE and ROA) recorded a mean (medium) value of 0.1226 (0.11135) and 0.0794 (0.0664) respectively. While for the leverage, it has recorded the mean of 0.4046 which indicated that Malaysia listed companies in average financed their assets by debt in around 40.46 percent. In terms of dividend per share, it showed that Malaysia listed companies in average has paid out the dividend of RM 0.10 per shares to their shareholders. Lastly, the investment growth (ratio of CAPEX to market value of firm) has recorded the mean of 38.21 percent.
For the descriptive statistic of year 2007 shown in Table 4.2, it showed that the mean (medium) of Tobin?s Q is 1.1462 (0.726980). This indicated that their market value was more than the recorded value of the assets of the company, in other words, Malaysia listed companies in average has been overvalued by the market in 2007. The profitability ratios (ROE and ROA)
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The Impact of Derivatives on Firm Value
recorded the mean (medium) value of 15.16 percent (13.18 percent) and 9.57 percent (7.28 percent) respectively. While the mean value of leverage was 0.2676777 which indicated that Malaysia listed companies on average financed their assets by debt in around 26.77 percent. In terms of the investment growth, it has recorded the mean of 26.04 percent. Lastly, Malaysia listed companies in average paid RM 0.10 dividends per share to their shareholders in 2007.
Followed by the descriptive statistic of 2008 shown in Table 4.3, it showed that the mean (median) of Tobin?s Q ratio was 0.7369. This indicated that their market value was less than the recorded value of the assets of the company, in other words, Malaysia listed companies have been undervalued by the market. While the mean of profitability ratios (ROE and ROA) were 11.30 percent (11.68 percent) and 7.59 percent (6.80 percent) respectively. Whereas the mean of leverage was 0.56675 which indicated that 56.69 percent of the assets of Malaysia listed companies were financed by debt. In terms of the investment growth, the mean value was recorded at 0.523241 or 52.32 percent. Lastly, Malaysia listed companies in average have paid out dividend of RM 0.09 per share to their shareholders in 2008.
Lastly in Table 4.4, it shows the descriptive statistic for the year 2009. The mean of Tobin?s Q for Malaysia listed companies was 0.7991, this indicated that the Malaysia listed companies in average has been undervalued by the market in 2009. The profitability ratios (ROE and ROA) have recorded a mean (median) value of 10.32 percent (9.64 percent) and 6.66 percent (5.69 percent) respectively. Whereas the mean value of leverage was 0.379421 which indicated that 37.94 percent of the assets of Malaysia listed companies were financed by debt. In terms of the investment growth, the mean value was recorded at 36.28 percent. Besides that, Malaysia listed companies in average has paid out the dividend of RM 0.11 per share to their shareholders in 2009.
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The Impact of Derivatives on Firm Value
Table 4.1: Descriptive Statistic for Pooled Data
Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations
TOBIN?S Q 0.863412 0.557654 8.836000 -0.403709 1.070044 3.243932 17.71621 9699.715 0.000000 777.0706 1029.350 900
SIZE 9.026994 8.969425 10.85350 5.842217 0.572208 -0.036297 6.593048 484.3223 0.000000 8124.295 294.3524 900
ROE 0.122577 0.111350 2.326960 -1.890900 0.220637 1.003207 47.88707 75707.81 0.000000 110.3197 43.76378 900
ROA LEVERAGE 0.079398 0.404621 0.066443 0.124200 2.701200 34.36550 -0.412100 -0.684500 0.127190 1.327634 10.09638 19.28258 205.1491 479.5712 1547700. 0.000000 71.45822 14.54348 900 8572776. 0.000000 364.1589 1584.588 900
INVESTMET GROWTH 0.382106 0.101006 8.787456 0.000100 0.767974 4.353325 30.50664 31215.79 0.000000 343.8953 530.2163 900
DPS 0.101050 0.040000 2.450000 0.000000 0.211906 5.873345 49.73962 87096.64 0.000000 90.94500 40.36875 900
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The Impact of Derivatives on Firm Value
Table 4.2: Descriptive Statistic for 2007
Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations
TOBIN?S Q 1.146171 0.726980 20.13330 -0.290100 1.687333 6.078472 58.94660 40972.66 0.000000 343.8514 851.2811 300
SIZE 8.968566 8.926669 10.83070 5.842217 0.621360 -0.556215 7.656380 286.4922 0.000000 2690.570 115.4404 300
ROE 0.151579 0.131750 2.326960 -0.673300 0.224883 5.274280 51.26643 30511.50 0.000000 45.47378 15.12115 300
ROA LEVERAGE 0.095665 0.267677 0.072769 0.096440 2.701200 3.044900 -0.405100 -0.684500 0.176707 0.457681 10.87435 3.128022 159.5770 15.28245 312366.9 0.000000 28.69947 9.336368 300 2374.958 0.000000 80.30315 62.63222 300
INVESTMENT GROWTH 0.260382 0.077100 2.273400 0.000100 0.447515 2.684497 10.15063 999.4693 0.000000 78.11474 59.88058 300
DPS 0.101677 0.040000 2.450000 0.000000 0.221612 6.473189 58.02580 39943.09 0.000000 30.50310 14.68445 300
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The Impact of Derivatives on Firm Value
Table 4.3: Descriptive Statistic for 2008
Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations
TOBIN?S Q 0.736890 0.430700 9.396400 -0.403709 1.098916 4.328630 28.90108 9322.676 0.000000 221.0671 361.0775 300
SIZE 9.037429 8.962243 10.84410 5.843506 0.557227 0.081503 6.574752 160.0678 0.000000 2711.229 92.84013 300
ROE 0.112971 0.116800 1.995400 -1.890900 0.234531 -1.428010 41.79082 18911.05 0.000000 33.89115 16.44644 300
ROA LEVERAGE 0.075936 0.566765 0.068019 0.168000 0.726900 34.36550 -0.412100 0.000000 0.096291 2.149144 0.521425 13.34520 14.91633 206.2192 1788.581 0.000000 22.78073 2.772314 300 525130.2 0.000000 170.0295 1381.027 300
INVESTMENT GROWTH 0.523241 0.129129 8.787456 0.000200 1.051162 3.805062 21.51589 5009.400 0.000000 156.9723 330.3772 300
DPS 0.092842 0.040000 1.450000 0.000000 0.173482 4.356782 27.33534 8351.690 0.000000 27.85270 8.998677 300
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The Impact of Derivatives on Firm Value
Table 4.4: Descriptive Statistic for 2009
Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations
TOBIN?S Q 0.799126 0.493094 8.750100 -0.212900 0.982379 3.615790 22.31386 5316.511 0.000000 239.7377 288.5555 300
SIZE 9.074988 8.984830 10.85350 7.835988 0.531055 0.776749 3.626742 35.07698 0.000000 2722.496 84.32395 300
ROE 0.103184 0.096361 1.700000 -1.858000 0.198686 -1.232071 48.51502 25971.12 0.000000 30.95513 11.80331 300
ROA 0.066594 0.056944 0.697100 -0.410700 0.087756 1.374339 16.84041 2488.903 0.000000 19.97807 2.302620 300
LEVERAGE 0.379421 0.122650 5.120300 0.000000 0.652305 3.306734 17.35362 3122.054 0.000000 113.8263 127.2249 300
INVESTMENT GROWTH 0.362754 0.099450 4.805500 0.000879 0.657876 3.174749 15.14826 2348.705 0.000000 108.8263 129.4076 300
DPS 0.108714 0.040000 2.360000 0.000000 0.235930 5.664781 43.81736 22430.20 0.000000 32.61420 16.64324 300
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The Impact of Derivatives on Firm Value
4.2
Pearson Correlation
Table 4.5 reports the Pearson correlation coefficients between the dependent variable (Tobin?s Q) and explanatory variables. It reported a set of bivariate correlation coefficients results between Tobin?s Q and all independent variables. Tobin?s q, proxy of the firm value, was neg atively and significantly correlated with interest rate derivative used at 5 percent level but was positively correlated with commodity and currency derivatives used. The correlation between interest rate derivative and Tobin?s Q was only -0.07. On the other hand, the correlation between Tobin?s Q and commodity derivative was 0.011; whereas the correlation between Tobin?s Q and currency derivatives was 0.03. ROA, ROE and DPS were found positively and significantly correlated with firm value at 1 percent level. The correlation between firm value and ROA was high at 0.517. While the correlation between firm value and ROE was also high at 0.475. The correlation between DPS and firm value was 0.456. Besides, firm size was also found to be negatively correlated with firm value where the correlation between the two variables was -0.059. On the other hand, firm value was negatively and significantly correlated with leverage and investment growth at 1 percent level. The correlation between firm value and leverage was 0.101. While the correlation between Tobin?s Q and investment growth was -0.117.
4.3
Ordinary Least Square Result
At first, we conducted a simple ordinary least square (OLS) as shown in Table 4.6. It presented the detail of OLS results with and without the adjustment of heteroskedasticity in 2007, 2008, 2009 and pooled data. The results were separated into two columns for each years and pooled
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The Impact of Derivatives on Firm Value
data. One is the normal OLS results before the adjustment of heteroskedasticity (OLS) while the other one is the OLS results with the adjustment of heteroskedasticity (With H-C).
The firm size was significantly (0.05) and negatively related with firm value in 2007 without the adjustment of heteroskedasticity but insignificant with the adjustment of heteroskedasticity. This indicated that the firm value would decrease as its firm size to increase. However in 2008, both OLS with and without the adjustment of heteroskedasticity were significant positively related to firm value at one percent and five percent level of significance. Whereas the result in 2009 showed that it was not significant at all. In the pooled data, negative relationship was significantly (0.01) shown on both with and without the adjustment of heteroskedasticity.
In terms of return on equity (ROE), it was not significant in all the three years and pooled data with and without the adjustment of
heteroskedasticity. In terms of the return on assets (ROA), the result showed that it was significantly and positively related to firm value in all the three years and also pooled data.
Besides that, both of the leverage and Investment growth were not significant in all the three years and pooled data without the adjustment of heteroskedasticity. As for dividend per share, it was significantly and positively related to firm value with and without the adjustment of heteroskedasticity in all the years (except 2008) and pooled data. It was consistent with the findings of Lang and Litzenberger (1989), Azhagaiah and Priya (2008), and Lintner (1956). They suggested that dividend announcement would affect the stock price of a firm, because market believed that valuable information about the firm future prospect and growth could be conveyed by an announcement of dividend.
In terms of the three types of derivatives, the commodity derivative was not significant in all the 3 years and also pooled data. While for the foreign
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The Impact of Derivatives on Firm Value
currency derivative, it was only significant in 2007 and this was consistent with the finding of Allayannis and Weston (2001), and Bartram et al (2006) which stated that FCD has significant impact (positive effect) on firm market value.
Whereas for the interest rate derivative, it was only the one of the derivatives which has the negative impact on firm value in 2007, 2008 and pooled data with the adjustment of heteroskedasticity. Our result supported the finding of Khediri (2010) in which there was a negative relationship between interest rate derivatives and firm value. However, this was not consistent with the findings of Singh (2009), and Batram et al (2006) which pointed out that firm that using interest rate derivatives have a positive valuation effect.
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The Impact of Derivatives on Firm Value
Table 4.5: Pooled Correlation Matrix Interest rate Commodity Currency Tobin?s Q Derivatives Derivatives Derivatives -0.070* 1 0.011 0.030 0.037 0.740 0.361 ** 0.115 0.176** 1 0.001 0.000 0.132** 1 0.000 1 Size -0.059 .0075 0.188** 0.000 0.044 0.184 0.070* 0.035 1 Leverage -0.101** 0.003 0.082* 0.014 -0.004 0.916 0.009 0.794 0.176** 0.000 1 ROA 0.517** 0.000 0.000 0.999 0.029 0.377 0.033 0.329 -0.067* 0.046 -0.135** 0.000 1 ROE 0.475** 0.000 0.038 0.251 0.051 0.125 0.077* 0.021 -0.002 0.948 -0.114** 0.001 0.802** 0.000 1 Investment Growth -0.117** 0.000 0.001 0.984 -0.031 0.351 -0.069* 0.037 0.055 0.101 0.406** 0.000 -0.139** 0.000 -0.111** 0.001 1 DPS 0.456** .000 -0.011 0.750 0.044 0.188 0.158** 0.000 0.095** 0.004 -0.084* 0.011 0.341** 0.000 0.413** 0.000 -0.110** 0.001 1
Tobin?s Q Interest rate Derivatives Commodity Derivatives Currency Derivatives Size Leverage ROA ROE Investment Growth DPS
*p<0.05, **p<0.01
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The Impact of Derivatives on Firm Value
Table 4.6: Regression Results of the Factors That Affect Firm Value Variable 2007 2008 2009 OLS With H-C OLS With H-C OLS With H-C Constant 4.1055 4.1055 -1.5763 -1.5763 0.7463 0.7463 -0.3730** 0.2129** 0.2129*** Size -0.3730 -0.0543 -0.0543 (0.1578) (0.2512) (0.1060) (0.0775) (0.0863) (0.0863) ROE 0.6464 0.6464 -0.4545 -0.4545 -0.2871 -0.2871 (0.9107) (1.0690) (0.4918) (0.9300) (0.3266) (0.4462) 1.3670* 5.8683*** 5.8682*** 6.2989*** 6.2989*** ROA 1.3670 (1.0740) (0.7236) (1.2728) (1.6088) (0.7827) (1.6668) Leverage -0.0708 -0.0708 -0.0022 -0.0022 0.0724 0.0724 (0.2199) (0.1207) (0.0304) (0.0211) (0.0723) (0.0601) Investment Growth -0.1661 -0.1661* 0.0663 0.0663 0.0469 0.0469 (0.2041) (0.0971) (0.0623) (0.0413) (0.0645) (0.0582) 1.7382*** 1.7382*** DPS 0.5729 0.5729 1.2593*** 1.2593*** (0.5055) (0.4439) (0.3685) (0.4377) (0.2094) (0.3318) Commodity Derivative -0.2274 -0.2274 0.0979 0.0979 0.0502 0.0502 (0.3908) (0.2353) (0.0989) (0.1163) (0.1694) (0.1144) 0.4722** Currency Derivative 0.4722 -0.0687 -0.0687 -0.0596 -0.0596 (0.2096) (0.3305) (0.1246) (0.1297) (0.0935) (0.0793) -0.402*** -0.402*** Interest rate Derivative -0.3845 -0.3845** -0.0563 -0.0563 (0.2396) (0.1556) (0.1458) (0.1075) (0.1105) (0.0923) R² 0.1905 0.1905 0.2425 0.2425 0.4993 0.4993 7.5826*** 7.5826*** 10.3172*** 10.3172**** 32.1267*** 32.1267*** F-test *sig at 0.1, **sig at 0.05, ***sig at 0.01, std error are given in parentheses Dependent variable: Firm Value (T obin?s Q) Pooled OLS With H-C 1.3817 1.3817 -0.099* -0.0990* (0.0522) (0.0530) 0.3083 0.3083 (0.2251) (0.5300) 2.9688*** 2.9688*** (0.3806) (1.0564) 0.0051 0.0051 (0.0240) (0.0146) -0.0393 -0.0393 (0.0411) (0.0287) 1.5908*** 1.5908*** (0.1512) (0.2516) -0.0155 -0.0155 (0.0753) (0.0366) -0.055 -0.055 (0.0645) (0.0609) -0.1487* -0.1487** (0.0760) (0.0712) 0.3650 0.3650 56.8381*** 56.8381***
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The Impact of Derivatives on Firm Value
4.4
Pooled Data Analysis
In this study, panel data technique was used. Table 4.7 shows the regression results of the model that examines the effect of the use of derivative on firm value. The model was derived based on pooled effect (PE), fixed effect (FE), and random effect (RE) methods. The original results of all the three methods that generated from E-view are shown in Appendix 1 (PE), Appendix 2 (FE), and Appendix 3 (RE). In order to choose which model is more suitable for estimating T obin?s Q equation, the Hausman specification test (Hausman, 1978)15 as shown in Table 4.8 was conducted to statistically test these three methods. If the model is correctly specified and individual effect are uncorrelated with the dependent variable, the fixed effect and random effect estimators should not be statistically different. The statistic reported in Table 4.8 showed that the null hypothesis, the individual effects were uncorrelated with the other regressors and was rejected in one percent significance level. The result suggested that the fixed effect model was most appropriate in estimating the Tobin?s Q equation.
From the results derived from fixed effect model, firm size was found to be significantly and negatively related to the firm value. This represented the larger the firm size, the lower the firm value. Our result supported the findings of Mak and Kusnadi (2005) in which there was an inverse relationship between firm value and firm size. However, it was not consistent with the findings of Ushijima (2003) in which the value of firm increased with its firm size.
Besides, we have observed a significant positive relationship between the leverage and firm value. It was consistent with the findings of Ward and Price (2006). They indicated that an increase in debt-equity ratio, shareholder returns would also to increase. However, Salehi and Biglar
15
Hausman, J. (1978). Specification tests in econometrics, Econometrica, 46, 1251-1271. 4-12
The Impact of Derivatives on Firm Value
(2009), and Rayan (2008) concluded that firm value and firm leverage were negatively correlated.
Furthermore, there was a significant positive relationship between firm value and ROA at one percent level of significance. Modigliani and Miller (1958) stated that a firm?s value could be maximized by using more debt in its capital structure; debt allowed firm to decrease their average cost of capital and enhance profitability as long as its ROA was greater than the before-tax interest paid on debt. ROE was found to be insignificant in determining the firm value.
In addition, we found that there was a negative relationship between firm value and investment growth at one percent level of significance. According to research done by Chung et al. (1998), market perceived that firms with low Tobin?s Q ratios having a lack of valuable or low profitable investment opportunities, therefore market reactions generally less positive about the announcements of capital expenditures increase by such firm; but tend to view favorably if it reduced capital expenditures. During the period of 2007-2009, Malaysia?s economy has been badly affected by the US subprime crisis, therefore the market may perceived the company within the country has lack of valuable investment opportunity and did not feel optimistic if firms increased their capital spending.
The results indicated that the dividend was positively related to firm value and statistically significant at five percent level. It was consistent with the findings of Lang and Litzenberger (1989), Azhagaiah and Priya (2008), and Lintner (1956). They suggested that an announcement of dividend will increase the stock price and vice versa. The reason was, managers were believed to hold reliable insider information about the future financial position of a company and they could convey this information to investor through dividend distributions. Thus, an announcement of a dividend was believed to convey certain valuable information about the firm future prospect and growth to the public.
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The Impact of Derivatives on Firm Value
In terms of the three types of derivatives, the results showed that interest rate derivative has no significant impact on firm value. It was consistent with the findings of Nelson et al. (2005). However, Singh found that lodging firms were positively exposed to interest rate risk. Therefore a further empirical research should be conducted on this argument.
Besides that, the commodity derivative was also insignificant related to the firm value. This result was consistent with the research of Jin and Jorion (2004), they found that hedging did not affect firm value and there were no differences in firm?s value between firm that hedge and firm that d id not hedge. Besides that, Nelson et al. (2005) also found out there was no abnormal return for firms hedging either by interest rate or commodity derivatives.
From the regression result, only the currency derivative was significantly related to the firm value; however, it was in negative relationship. This indicated that if the firms used FCD, they might experience loses. This was inconsistent with the finding of Allayannis and Weston (2001) and Bartram et al. (2006). The later researchers pointed out FCD has a significant positive effect on firm market value. However, our result supported the finding of Khediri (2010) in which derivative has a negative relationship with the firm value.
Furthermore, Nguyen and Faff (2003) discovered that the impact of FCD usage on exchange risk exposure was generally weak and lacks consistency. Bartram et al. (2004) revealed evidence of positive value effect of general derivatives use but only limited for firms without exposure. The impact of FCD usage, in particular, was found to be insignificant. Bodnar, Haty and Marston (1996)16 provided extensive survey evidence on corporate derivatives use. Their evidence suggested that firms typically hedged with derivatives but did so imperfectly.
16
Bodnar, G.M., Haty, G.S., & Marston, R.C. (1996). 1995 Wharton survey of derivatives usage by U.S. non-financial firms. Financial Management, 25(4), 113-133. 4-14
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Table 4.7: Pooled Data Analysis of Value Effects of Derivatives Use Decision Variables Constant Size Random 2.1403 -0.1626*** (0.058) ROE -0.0172 (0.1753) 2.1103*** ROA (0.2889) Leverage 0.0231 (0.0192) -0.1639*** Investment Growth (0.0404) 1.1048*** DPS (0.1411) Commodity Derivative -0.0005 (0.0594) Currency Derivative -0.0846 (0.0766) Interest rate Derivative -0.0384 (0.0958) R² 0.2091 Hausman Test 0.0000 56.8381*** 11.5807*** 26.1374*** F-test *sig at 0.10, **sig at 0.05, ***sig at 0.01, std error are given in parentheses Dependent Variable: Firm Value (Tobin?s Q) Pooled 1.3817 -0.0990* (0.0522) 0.3083 (0.2251) 2.9688*** (0.3806) 0.0051 (0.0240) -0.0393 (0.0411) 1.5908*** (0.1512) -0.0155 (0.0753) -0.055 (0.0645) -0.1487* (0.0760) 0.365 Fixed 3.0906 -0.2528*** (0.0854) -0.3049 (0.1927) 1.7880*** (0.3117) 0.0432** (0.0219) -0.2507*** (0.0509) 0.3811** (0.1782) 0.0045 (0.0650) -0.2134* (0.1261) 0.2885 (0.1867) 0.8579
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Table 4.8: Hausman Specification Test Correlated Random Effects - Hausman Test Pool: HM Test cross-section random effects Test Summary Cross-section random Chi-Sq. Statistic Chi-Sq. d.f. 111.869283 9 Prob. 0.0000
Cross-section random effects test comparisons: Variable INTDERIVATIVES? COMDERIVATIVES? CURDERIVATIVES? SIZE? LEVERAGE? ROA? ROE? INVESGROWTH? DPS? Fixed 0.288476 0.004511 -0.213413 -0.252805 0.043157 1.788026 -0.304914 -0.250748 0.381134 Random -0.038449 -0.000506 -0.084614 -0.162597 0.023077 2.110258 -0.017187 -0.163891 1.104780 Var(Diff.) 0.025644 0.000699 0.010048 0.003943 0.000108 0.013711 0.006400 0.000954 0.011865 Prob. 0.0412 0.8495 0.1988 0.1508 0.0534 0.0059 0.0003 0.0049 0.0000
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CHAPTER 5 CONCLUSION
5.1
Conclusion
The study examined the impact of derivatives on the sample of 300 Malaysia non-financial firms over the period 2007-2009. From the regression results, we concluded that interest rate derivatives and commodity derivatives have no significant impact on firm value, this result supported the finding of Nelson et al. (2005) in which the usage of these two derivatives have no effect on the firm?s market value. On the other hand, the currency derivatives were partially significant but it is negatively related to the firms? market value. In other words, if the firm performs hedging activities by using currency derivatives, it will lower down its market value. This result was inconsistent with the findings of Allayannis and Weston (2001), Pramborg (2003), Nelson et al. (2005), and Allayannis et al. (2009). However, from the research of Nguyen and Faff (2003) they found currency derivatives usage was generally weak and lack consistent.
In terms of other explanatory variables, firm size and investment growth have a strong significant impact on firm value but in negative relationship. For leverage, ROA, and dividend per share, there were significant positively related to the firms? market value.
Therefore, we made a conclusion for the hypotheses that we developed in chapter 3: 1. Interest rate derivatives: Do not reject H0. There is no evidence shows that interest rate derivative is positively related to firm value. 2. Currency derivatives: Do not reject H0. There is no evidence shows that currency derivative is positively related to firm value.
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3. Commodity derivatives: Do not reject H0. There is no evidence shows that commodity derivative is positively related to firm value.
From the results, it seems like the hedging activities is independent from the management especially both of the commodity and interest rate derivatives. While for the currency derivatives is valued at a discount. The question of why currency derivatives use is valued at discount in Malaysia deserves further research.
5.2
Implications
Our results showed that the use of financial derivatives towards the potential impact on firms value in a broad sample of non-financial firms from 2007 to 2009. The result from the finding may be implying that how the firms truly use of financial derivatives and shareholder value influence by the finance policy.
From the regression results, the interest rate derivatives and commodity derivatives were not significantly and positively related to firm value, this implied that the use of interest rate derivatives and commodity derivatives did not have any impact on firms market value, hence whether or not the company has used these two derivatives would not improve company value and maximize shareholder wealth. Shareholder may find that interest rate derivatives and commodity derivatives are useless for firms and request management team to cut off the expenditure spend on derivatives and transfer the capital to other more profitable investments. Even result showed insignificant, it is still consistent with the findings of Nelson et al. (2005) and Khediri (2010) but it is inconsistent with other finding such as Ameer (2009), Covitz and Sharpe (2005), Bartram et al. (2006), Carter et al. (2002).
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The currency derivative was partially significant but it was negatively related to the firms? market value. In other words, the currency derivatives has a negative impact on Malaysia?s firm value, which means if the firm performs hedging activities by using currency derivatives, it will lower down its market value. This implies that management of the company may avoid using currency derivatives. Unlike interest rate and commodity derivatives, shareholder may avoid to invest in firms that use currency derivative as policy in managing currency risk. Firms with currency risk may have to choose other instruments to hedge the risk or alternative method to minimize it. Our result did not consistent with the findings of Allyannis and Weston (2001), Pramborg (2003), Nelson et al. (2005), and Allyannis et al. (2009). However, from the research of Nguyen and Faff (2003) they found currency derivatives usage was generally weak and lack consistent.
5.3
Limitations and Recommendations
We find some limitations on this study. Firstly, our data collection process was only restricted on companies? financial reports. All of the data that we needed in the research was based on the financial information of the Malaysia top 300 non-financial firms. Therefore, we collected the data such as derivative usage, ROA, total assets, market capitalization, net profits, current liabilities and others by looking at the companies? financial report one by one. This was time consuming because we need to collect the financial data of 300 companies for 3 years. Besides that, the financial report is less accuracy in communicating the real value of the enterprise and its future performance potential. Therefore, in order to improve the accuracy of the data that we collected, our suggestion is to use the online databases which are chargeable, such as OSIRIS and Bursa Station. These two online databases provide the financial statements for all the Malaysia companies in detailed. It will also show the financial reports of a particular company for few years in a page, it is easier for the analyst to collect data and compare the performance of a company across the time
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The Impact of Derivatives on Firm Value
series. However, these two online databases are chargeable, we have to pay before we can access to it.
Secondly, differences in accounting methods between companies will make it difficult in comparing the performance of the companies. For example, some firms may use LIFO method to prepare their financial report while some may use average cost method. Then direct comparison of financial data such as cost of goods sold between two companies may be misleading. The misleading value of cost of goods sold will have an impact on the gross profit and hence the net profit. Thus, it will lower down the accuracy of analysis by comparing the companies with different accounting method.
Besides that, some of the journals are chargeable. In Chapter 2, we conducted a literature review by reading on the journals that done by other researchers on the topic which was similar to our research. For some of the important journal which is directly discussing their findings on the impact on derivatives on firm value, we only found its paragraph of abstract but not in full journals, we are required to pay for it prior to access to the whole journals. Students may not afford to pay for it. Our suggestion is that the faculty should provide more and more free trial accessing to the external database which could let the students easily find the journals in completing their thesis.
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APPENDICES
Appendix 1: Result of Pooled Effect
Dependent Variable: TOBINSQ? Method: Pooled Least Squares Date: 03/01/11 Time: 18:38 Sample: 2007 2009 Included observations: 3 Cross-sections included: 300 Total pool (balanced) observations: 900 Variable C INTDERIVATIVES? COMDERIVATIVES? CURDERIVATIVES? SIZE? LEVERAGE? ROA? ROE? INVESGROWTH? DPS? R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) Coefficient 1.381719 -0.148699 -0.015490 -0.054995 -0.099007 0.005128 2.968806 0.308347 -0.039265 1.590784 0.364986 0.358564 0.856995 653.6521 -1133.126 56.83813 0.000000 Std. Error 0.468759 0.076007 0.075347 0.064544 0.052188 0.024043 0.380586 0.225074 0.041087 0.151171 t-Statistic 2.947609 -1.956399 -0.205578 -0.852067 -1.897131 0.213266 7.800624 1.369983 -0.955676 10.52305 Prob. 0.0033 0.0507 0.8372 0.3944 0.0581 0.8312 0.0000 0.1710 0.3395 0.0000 0.863412 1.070044 2.540280 2.593640 2.560664 0.820250
Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat
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Appendix 2: Result of Fixed Effect
Dependent Variable: TOBINSQ? Method: Pooled Least Squares Date: 03/01/11 Time: 18:45 Sample: 2007 2009 Included observations: 3 Cross-sections included: 300 Total pool (balanced) observations: 900 Variable C INTDERIVATIVES? COMDERIVATIVES? CURDERIVATIVES? SIZE? LEVERAGE? ROA? ROE? INVESGROWTH? DPS? Fixed Effects (Cross) 1--C 2--C 3--C 4--C 5--C 6--C 7--C 8--C 9--C 10--C 11--C 12--C 13--C 14--C 15--C 16--C 17--C 18--C 19--C 20--C 21--C 22--C 23--C 24--C 25--C 26--C 27--C 28--C 29--C 30--C Coefficient 3.090641 0.288476 0.004511 -0.213413 -0.252805 0.043157 1.788026 -0.304914 -0.250748 0.381134 0.301243 0.323240 0.414843 -0.226266 0.900720 0.407761 2.794695 0.876661 0.640940 0.891262 -0.128941 -0.010897 6.764876 0.126781 0.096075 2.867060 0.105850 4.707487 -0.516373 -0.235599 -0.350889 -0.168716 0.387331 0.580395 0.027387 -0.097769 1.768882 0.351990 0.110320 1.452386 Std. Error 0.769901 0.186593 0.065038 0.126143 0.085447 0.021865 0.311705 0.192656 0.050890 0.178242 t-Statistic 4.014335 1.546018 0.069360 -1.691834 -2.958603 1.973835 5.736271 -1.582683 -4.927235 2.138289 Prob. 0.0001 0.1226 0.9447 0.0912 0.0032 0.0489 0.0000 0.1140 0.0000 0.0329
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31--C 32--C 33--C 34--C 35--C 36--C 37--C 38--C 39--C 40--C 41--C 42--C 43--C 44--C 45--C 46--C 47--C 48--C 49--C 50--C 51--C 52--C 53--C 54--C 55--C 56--C 57--C 58--C 59--C 60--C 61--C 62--C 63--C 64--C 65--C 66--C 67--C 68--C 69--C 70--C 71--C 72--C 73--C 74--C 75--C 76--C 77--C 78--C 79--C 80--C 81--C 82--C 83--C
0.865832 0.066042 -0.300108 0.826531 -0.377849 0.298821 -0.254500 -0.105425 1.936487 0.090427 1.123728 -0.615710 -0.328558 -0.517337 0.420870 -0.144103 -1.039050 1.340976 -0.137368 -0.281652 -0.332505 -0.277337 0.064760 0.684611 -0.228950 0.257205 0.401800 1.791787 -0.149544 2.164580 -0.440664 0.092259 0.748344 0.739806 0.006138 1.244382 0.858343 0.386741 1.418879 0.423631 0.711054 0.211605 1.832551 1.427216 0.509018 0.649600 0.488031 0.464006 0.289630 2.891073 0.854196 0.932140 0.437455
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84--C 85--C 86--C 87--C 88--C 89--C 90--C 91--C 92--C 93--C 94--C 95--C 96--C 97--C 98--C 99--C 100--C 101--C 102--C 103--C 104--C 105--C 106--C 107--C 108--C 109--C 110--C 111--C 112--C 113--C 114--C 115--C 116--C 117--C 118--C 119--C 120--C 121--C 122--C 123--C 124--C 125--C 126--C 127--C 128--C 129--C 130--C 131--C 132--C 133--C 134--C 135--C 136--C
0.112123 -0.188489 -0.100831 -0.148119 3.543283 0.732303 0.328476 0.548549 -0.211429 0.312736 0.119293 0.744009 0.497300 0.686946 0.738498 0.212651 0.854341 0.880783 -0.023158 0.293555 0.342462 1.137522 1.157321 0.428442 0.069574 0.476993 0.051904 0.210015 2.226218 0.716392 0.736729 0.615652 0.426039 1.356178 -0.595799 0.081541 1.188969 -0.476879 -0.503446 -0.125268 -0.469239 -0.289715 -0.517805 -0.173951 -0.735252 -0.095181 -0.283080 -0.843831 -0.422299 -0.403663 -0.805084 -0.907993 -0.177528
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137--C 138--C 139--C 140--C 141--C 142--C 143--C 144--C 145--C 146--C 147--C 148--C 149--C 150--C 151--C 152--C 153--C 154--C 155--C 156--C 157--C 158--C 159--C 160--C 161--C 162--C 163--C 164--C 165--C 166--C 167--C 168--C 169--C 170--C 171--C 172--C 173--C 174--C 175--C 176--C 177--C 178--C 179--C 180--C 181--C 182--C 183--C 184--C 185--C 186--C 187--C 188--C 189--C
-0.839133 -0.567085 -0.371744 0.370768 -0.744399 -0.291946 -0.513954 0.435673 -0.319179 -0.530779 0.873075 0.564812 0.176746 -1.204041 -0.383972 -0.682271 -0.560246 0.063033 -0.044211 -0.903405 -0.201357 0.453771 -0.123317 1.678678 -0.619737 -0.617862 -0.770390 -0.887731 -1.175807 -1.293682 -0.795160 0.145443 -0.417252 -0.080232 -0.882661 -0.704096 -0.024329 -1.012929 -0.590030 0.137834 -0.729940 0.045828 -0.170101 -0.738802 0.253380 0.768510 -0.168500 -0.658571 -0.643194 -0.310412 -0.389592 -0.536898 -0.179795
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190--C 191--C 192--C 193--C 194--C 195--C 196--C 197--C 198--C 199--C 200--C 201--C 202--C 203--C 204--C 205--C 206--C 207--C 208--C 209--C 210--C 211--C 212--C 213--C 214--C 215--C 216--C 217--C 218--C 219--C 220--C 221--C 222--C 223--C 224--C 225--C 226--C 227--C 228--C 229--C 230--C 231--C 232--C 233--C 234--C 235--C 236--C 237--C 238--C 239--C 240--C 241--C 242--C
-0.752452 -0.447405 -0.537504 -0.307335 -0.019275 0.407213 -0.666976 0.319639 -0.450747 -0.197372 -0.247410 -0.644115 0.267128 -0.379032 -0.240242 -0.753454 -0.364616 -0.784357 -0.065541 -1.047176 -0.389935 -0.646241 -0.448688 -0.274207 0.107559 0.065229 -0.771804 -0.461638 -0.369913 0.078596 -1.020166 -0.457870 -0.728460 -0.380402 -0.879278 0.044452 -0.595089 -0.990054 -0.147925 -0.806377 -0.718580 -0.699646 1.762189 -0.498581 0.208342 -1.003470 -0.740667 -0.331241 -0.560938 -0.602584 -0.516947 -0.712449 -0.782752
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243--C 244--C 245--C 246--C 247--C 248--C 249--C 250--C 251--C 252--C 253--C 254--C 255--C 256--C 257--C 258--C 259--C 260--C 261--C 262--C 263--C 264--C 265--C 266--C 267--C 268--C 269--C 270--C 271--C 272--C 273--C 274--C 275--C 276--C 277--C 278--C 279--C 280--C 281--C 282--C 283--C 284--C 285--C 286--C 287--C 288--C 289--C 290--C 291--C 292--C 293--C 294--C 295--C
-0.676290 -0.315631 0.627902 -0.322376 -0.972990 -0.728781 -0.621609 -0.790601 -0.959913 -0.729204 -0.025211 -0.187031 -0.475599 -0.500342 -0.995594 0.095173 -0.954220 -0.532140 -0.606273 -0.563906 -0.297057 -0.394075 -0.499422 -0.395952 -0.928782 -0.832072 -0.399136 1.665149 -0.622900 -0.673843 -0.392805 0.633924 0.083287 -0.792756 -0.669045 1.825006 -0.564215 -0.502314 -0.921908 -0.431008 -0.773042 0.064309 -0.803729 -0.545550 -0.549413 -0.680543 0.218466 -0.714958 -0.227884 -0.393114 -0.719318 -0.725600 -0.688328
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296--C 297--C 298--C 299--C 300--C
-0.460292 -0.868783 -1.049521 0.255122 -1.012892 Effects Specification
Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.857860 0.783783 0.497561 146.3120 -459.5507 11.58074 0.000000 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat 0.863412 1.070044 1.707890 3.356713 2.337752 2.729316
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Appendix 3: Random Effect
Dependent Variable: TOBINSQ? Method: Pooled EGLS (Cross-section random effects) Date: 03/01/11 Time: 18:49 Sample: 2007 2009 Included observations: 3 Cross-sections included: 300 Total pool (balanced) observations: 900 Swamy and Arora estimator of component variances Variable C INTDERIVATIVES? COMDERIVATIVES? CURDERIVATIVES? SIZE? LEVERAGE? ROA? ROE? INVESGROWTH? DPS? Random Effects (Cross) 1--C 2--C 3--C 4--C 5--C 6--C 7--C 8--C 9--C 10--C 11--C 12--C 13--C 14--C 15--C 16--C 17--C 18--C 19--C 20--C 21--C 22--C 23--C 24--C 25--C 26--C 27--C 28--C Coefficient 2.140348 -0.038449 -0.000506 -0.084614 -0.162597 0.023077 2.110258 -0.017187 -0.163891 1.104780 Std. Error 0.521649 0.095776 0.059419 0.076579 0.057953 0.019235 0.288876 0.175262 0.040446 0.141088 t-Statistic 4.103044 -0.401447 -0.008518 -1.104929 -2.805685 1.199733 7.305075 -0.098062 -4.052077 7.830450 Prob. 0.0000 0.6882 0.9932 0.2695 0.0051 0.2306 0.0000 0.9219 0.0001 0.0000
0.311254 0.322072 0.364946 -0.044834 0.494957 0.061310 1.115054 0.555165 0.452285 0.413031 0.014232 0.135121 3.875115 0.075729 -0.132118 1.491621 0.066211 3.531785 -0.571820 -0.060569 -0.285849 -0.129019 0.094648 0.440103 0.135427 -0.161409 1.321489 -0.054302 A-9
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29--C 30--C 31--C 32--C 33--C 34--C 35--C 36--C 37--C 38--C 39--C 40--C 41--C 42--C 43--C 44--C 45--C 46--C 47--C 48--C 49--C 50--C 51--C 52--C 53--C 54--C 55--C 56--C 57--C 58--C 59--C 60--C 61--C 62--C 63--C 64--C 65--C 66--C 67--C 68--C 69--C 70--C 71--C 72--C 73--C 74--C 75--C 76--C 77--C 78--C 79--C 80--C 81--C
0.047974 1.245901 0.729868 -0.172387 -0.352946 0.743936 -0.675588 -0.066785 -0.379489 -0.276894 1.499833 0.108602 0.800861 -0.563678 -0.259531 -0.221306 0.140497 -0.191708 -0.778597 0.766400 -0.294066 -0.544681 -0.262472 -0.336806 -0.010441 0.409532 -0.215624 0.242950 0.613819 1.473131 -0.060171 1.732958 -0.424247 0.036629 0.605059 0.769380 0.016111 1.140556 0.610549 0.102151 1.326156 0.314060 0.362008 0.041730 1.390021 0.780817 0.395938 0.465403 0.440384 0.266515 0.199272 2.124273 0.771599 A-10
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82--C 83--C 84--C 85--C 86--C 87--C 88--C 89--C 90--C 91--C 92--C 93--C 94--C 95--C 96--C 97--C 98--C 99--C 100--C 101--C 102--C 103--C 104--C 105--C 106--C 107--C 108--C 109--C 110--C 111--C 112--C 113--C 114--C 115--C 116--C 117--C 118--C 119--C 120--C 121--C 122--C 123--C 124--C 125--C 126--C 127--C 128--C 129--C 130--C 131--C 132--C 133--C 134--C
0.966659 0.285123 0.130025 0.137558 -0.197766 -0.096499 3.120912 0.466255 0.276826 0.551145 -0.224216 0.230851 -0.008401 0.467668 0.062354 0.514802 0.582128 -0.002468 0.673211 0.684898 0.032217 0.238878 0.134824 0.755811 0.894520 0.255555 0.090038 0.456292 -0.032950 -0.100113 1.587289 0.589604 0.478073 0.420072 0.368225 1.127364 -0.446048 0.128693 0.907737 -0.185230 -0.057301 0.065438 -0.179873 -0.198579 -0.373722 -0.156274 -0.529064 -0.032692 -0.025527 -0.404927 -0.360689 -0.109004 -0.614930 A-11
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135--C 136--C 137--C 138--C 139--C 140--C 141--C 142--C 143--C 144--C 145--C 146--C 147--C 148--C 149--C 150--C 151--C 152--C 153--C 154--C 155--C 156--C 157--C 158--C 159--C 160--C 161--C 162--C 163--C 164--C 165--C 166--C 167--C 168--C 169--C 170--C 171--C 172--C 173--C 174--C 175--C 176--C 177--C 178--C 179--C 180--C 181--C 182--C 183--C 184--C 185--C 186--C 187--C
-0.485634 0.082016 -0.558596 -0.129232 -0.247248 0.193347 -0.755596 -0.309617 -0.483759 0.404441 -0.029039 -0.411072 0.698865 0.737446 0.336541 -0.787918 -0.288598 -0.675739 -0.409079 0.413411 0.120313 -0.402707 0.003425 0.526791 -0.114078 1.431381 -0.452609 -0.290879 -0.326266 -0.518227 -0.651611 -0.810491 -0.339580 0.296811 -0.240750 -0.104518 -1.060802 -0.310676 0.289933 -0.730357 -0.409113 0.245272 -0.640560 -0.207544 -0.032968 -0.543389 0.086429 0.668291 -0.085389 -0.715069 -0.435109 -0.193066 -0.301756 A-12
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188--C 189--C 190--C 191--C 192--C 193--C 194--C 195--C 196--C 197--C 198--C 199--C 200--C 201--C 202--C 203--C 204--C 205--C 206--C 207--C 208--C 209--C 210--C 211--C 212--C 213--C 214--C 215--C 216--C 217--C 218--C 219--C 220--C 221--C 222--C 223--C 224--C 225--C 226--C 227--C 228--C 229--C 230--C 231--C 232--C 233--C 234--C 235--C 236--C 237--C 238--C 239--C 240--C
-0.568220 -0.060373 -0.597850 -0.443565 -0.320869 -0.406533 0.106080 0.261031 -0.507544 0.183375 -0.541435 -0.119403 -0.226681 -0.635571 0.100866 -0.397147 -0.260167 -0.596005 -0.169752 -0.594734 -0.225263 -0.781463 -0.219342 -0.409492 -0.411928 -0.191529 0.072010 0.251908 -0.582210 -0.411247 -0.369527 -0.020186 -0.773694 -0.335504 -0.551342 -0.333941 -0.717805 -0.079165 -0.434587 -0.752317 -0.004802 -0.842688 -0.753515 -0.593562 1.382729 -0.338059 0.252212 -0.882727 -0.583308 -0.198641 -0.443601 -0.535815 -0.357195 A-13
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241--C 242--C 243--C 244--C 245--C 246--C 247--C 248--C 249--C 250--C 251--C 252--C 253--C 254--C 255--C 256--C 257--C 258--C 259--C 260--C 261--C 262--C 263--C 264--C 265--C 266--C 267--C 268--C 269--C 270--C 271--C 272--C 273--C 274--C 275--C 276--C 277--C 278--C 279--C 280--C 281--C 282--C 283--C 284--C 285--C 286--C 287--C 288--C 289--C 290--C 291--C 292--C 293--C
-0.443328 -0.485546 -0.599012 -0.228617 0.665572 -0.318975 -0.721582 -0.505645 -0.397068 -0.588341 -0.564128 -0.463018 0.376241 -0.158865 -0.399923 -0.301952 -0.622614 0.255140 -0.689710 -0.359838 -0.493754 -0.423549 -0.263155 -0.373384 -0.326659 -0.215785 -0.646957 -0.630597 -0.312189 1.485541 -0.492894 -0.451038 -0.425832 0.712050 0.031178 -0.520961 -0.517702 1.704332 -0.526201 -0.507154 -0.799845 -0.463540 -0.562513 -0.042638 -0.665719 -0.361270 -0.370416 -0.610728 0.153061 -0.557896 -0.069529 -0.220445 -0.630144 A-14
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294--C 295--C 296--C 297--C 298--C 299--C 300--C
-0.556228 -0.551743 -0.327792 -0.344366 -0.817212 0.203058 -0.538018 Effects Specification S.D. Rho 0.6324 0.3676
Cross-section random Idiosyncratic random Weighted Statistics R-squared Adjusted R-squared S.E. of regression F-statistic Prob(F-statistic) 0.209055 0.201057 0.525530 26.13744 0.000000
0.652601 0.497561
Mean dependent var S.D. dependent var Sum squared resid Durbin-Watson stat
0.347853 0.587949 245.8016 1.757847
Unweighted Statistics R-squared Sum squared resid 0.312392 707.7890 Mean dependent var Durbin-Watson stat 0.863412 0.610467
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doc_477523194.pdf
Enterprise value (EV), Total enterprise value (TEV), or Firm value (FV) is an economic measure reflecting the market value of a whole business. It is a sum of claims of all claimants: creditors (secured and unsecured) and equityholders (preferred and common).
THE IMPACT OF DERIVATIVES ON FIRM VALUE
CHEE MUN FEI KAM MEI KUAN LAI YEW KEAN POH ENG MING TAN HOAY SHAN
BACHELOR OF FINANCE (HONS)
UNIVERSITI TUNKU ABDUL RAHMAN FACULTY OF ACCOUNTANCY AND MANAGEMENT DEPARTMENT OF ECONOMICS APRIL 2011
THE IMPACT OF DERIVATIVES ON FIRM VALUE
BY CHEE MUN FEI KAM MEI KUAN LAI YEW KEAN POH ENG MING TAN HOAY SHAN
A research project submitted in partial fulfillment of the requirement for the degree of BACHELOR OF FINANCE (HONS) UNIVERSITI TUNKU ABDUL RAHMAN FACULTY OF ACCOUNTANCY AND MANAGEMENT DEPARTMENT OF ECONOMICS APRIL 2011
The Impact of Derivatives on Firm Value
Copyright @ 2011 ALL RIGHTS RESERVED. No part of this paper may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, graphics, electronic, mechanical, photocopying, recording, scanning, or otherwise, without the prior consent of the authors.
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DECLARATION
We hereby declare that: (1) This UBFZ3026 Research Project is the end result of our own work and that due acknowledgement has been given in the references to ALL sources of information be they printed, electronic, or personal. (2) No portion of this research project has been submitted in support of any application for any other degree or qualification of this or any other university, or other institutes of learning. (3) Equal contribution has been made by each group member in completing the research project. (4) The word count of this research report is 14590 words.
Name of Student: 1. Chee Mun Fei 2. Kam Mei Kuan 3. Lai Yew Kean 4. Poh Eng Ming 5. Tan Hoay Shan
Student ID: 09 UKB 07265 09 UKB 07267 09 UKB 07270 08 UKB 07752 09 UKB 06707
Signature:
Date: 20 April 2011
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ACKNOWLEDGEMENT
First of all, we would like to take this opportunity to acknowledge the contribution provided by various authorities who provided guidelines to help us in completing this research project.
We would like to express our deepest appreciation to our supervisors for this research project, Dr. Maran Marimuthu who has guided us throughout the entire research. His expertise, excellent guidance and invaluable comments or suggestion greatly assisted us for the completion of the research project. In addition, we also would like to thank Mr. Ng Kean Kok who is our second examiner for providing useful advices to us in conducting the research study.
Furthermore, we would like to express our appreciation to our families, friends and all the others for their assistance, support and encouragement for helping us to successfully complete our dissertation.
Last but not the least, we would like to thank our group members mutually in this research projects who are willing to work hard together to complete this project.
Thank you.
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TABLE OF CONTENTS Page Copyright Page Declaration Acknowledgement Table of Contents List of Table List of Figures List of Appendices List of Abbreviations Preface Abstract CHAPTER 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 INTRODUCTION Introduction Background of the Study Derivatives in Malaysia Problem Statement Research Questions Research Objectives Chapter Layout 1-1 1-1 1-3 1-6 1-7 1-7 1-8 ii iii iv v ix x xi xii xv xvi
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CHAPTER
2 2.1 2.2 2.3
LITERATURE REVIEW Definition of Derivatives The Use of Derivatives to Hedge Risk Research Theory 2.3.1 Interest Rate Derivatives 2.3.2 Foreign Currency Derivatives 2.3.3 Commodity Derivatives 2-2 2-3 2-4 2-1 2-1
2.4
Empirical Discussion 2.4.1 Interest Rate Derivatives 2.4.2 Foreign Currency Derivatives 2.4.3 Commodity Derivatives 2.4.4 Firm Size 2.4.5 Leverage 2.4.6 Investment Growth 2.4.7 Dividend Per Share 2.4.8 Profitability 2-5 2-8 2-10 2-12 2-13 2-15 2-16 2-18
CHAPTER 3 3.1 3.2 3.3
RESEARCH METHODOLOGY Introduction Research Design Data Collection Method 3-1 3-1 3-1
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3.4
Variable Specification 3.4.1 Dependent Variable 3.4.2 Independent Variables 3.4.3 Control Variables 3-2 3-2 3-2
3.5
Data Analysis Technique 3.5.1 Tobin?s Q 3.5.2 Multivariate Analysis 3.5.3 White Heteroskedasticity-Consistent Standard Error and Covariance 3.5.4 Panel Data Techniques 3.5.5 Hausman Specification Test 3-7 3-8 3-10 3-4 3-5
3.6
Hypotheses Development 3.6.1 Interest Rate Derivatives 3.6.2 Foreign Currency Derivatives 3.6.3 Commodity Derivatives 3-11 3-12 3-13
CHAPTER
4 4.1 4.2 4.3 4.4
DATA ANALYSIS Descriptive Statistic Pearson Correlation Ordinary Least Square Result Pooled Data Analysis 4-1 4-7 4-7 4-12
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CHAPTER
5 5.1 5.2 5.3
CONCLUSION Conclusion Implications Limitations and Recommendations 5-1 5-2 5-3 R1 A1
References Appendices
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LIST OF TABLES
Table 1.1 4.1 4.2 4.3 4.4 4.5 4.6 4.7 The Different Types of Derivatives Traded at BMD Descriptive Statistic for Pooled Data Descriptive Statistic for 2007 Descriptive Statistic for 2008 Descriptive Statistic for 2009 Pooled Correlation Matrix Regression Results of the Factors That Affect Firm Value Pooled Data Analysis of Value Effects of Derivatives Use Decision 4.8 Hausman Specification Test
Page 1-5 4-3 4-4 4-5 4-6 4-10 4-11 4-15
4-16
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LIST OF FIGURES
Figure 3.1 Conceptual Framework
Page 3-7
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LIST OF APPENDICES
Appendix Appendix 1: Result of Pooled Effect Appendix 2: Result of Fixed Random Effect Appendix 3: Result of Random Effect
Page A-1 A-2 A-9
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LIST OF ABBREVIATIONS
ANOVA BMD CAPEX CEO CP CPO COMMEX DFFITS DPS ECM EPS EVA GMM GDP FCD FCPO FE FKB3 FKLI FMG3 FMG5 FPKO FTSE FUPO
Analysis of Variance Bursa Malaysia Derivatives Berhad Capital Expenditures Chief Executive Officer Commodity Price Crude Palm Oil Commodity and Monetary Exchange Difference between the Fitted Values Dividend per Share Random Effect Model Earning per Share Economic Value Added Generalized Method of Moments Gross Domestic Product Foreign Currency Derivatives Crude Palm Oil Futures Fixed Effect 3 Month Kuala Lumpur Interbank Offered Rate Futures FTSE Bursa Malaysia KKLCI Futures 3-Year Malaysian Government Securities Futures 5-Year Malaysian Government Securities Futures Crude Palm Kernel Oil Futures Financial Times and London Stock Exchange USD Crude Palm Oil Futures
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FX IR IRD JSE KLCE KLCI KLSE KLOFFE LR MDEX MME MVA MVE NPV OKLI OLS OSIRIS PE PS RE REIT R&D ROA ROE SGX
Foreign Exchange Interest Rate Interest Rate Derivatives Johannesburg Stock Exchange Kuala Lumpur Commodities Exchange Kuala Lumpur Composite Index Kuala Lumpur Stock Exchange Kuala Lumpur Options and Financial Futures Exchange Likelihood Ratio Malaysian Derivatives Exchange Malaysian Monetary Exchange Market Value Added Market Value Net Present Value FTSE Bursa Malaysia KLCI Options Ordinary Least Squares Online Search Information Retrieval Information Storage Pooled Effect Preferred Stock Random Effect Real Estate Investment Trust Research and Development Return on Asset Return on Equity Singapore Exchange
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SSFs SMEs TA TSE UK US USD
Single Stock Futures Small and Medium-sized Enterprise Total Assets Tehran Stock Exchange United Kingdom United State United State Dollar
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PREFACE
Derivative is the financial instrument in which the value is derived from an underlying asset such as interest rate, common stock, foreign exchange rate, commodity, etc. The use of derivatives by non-financial firms was sharply increasing over the past few decades. The purpose of using derivatives by a company is to hedge the risk they are facing in their daily business operations. For example, derivatives are used to hedge the interest rate risk because the fluctuation of interest rate may incur a higher cost of debt to the firm. Anyhow, do the firm hedging activities lead to enhance or improve the firm value? It has been an argument among many researchers in the past. Whether derivatives will increase the firm value is still on the debate. Therefore, we have conducted this research to discover whether it will increase the market value of a firm by using financial derivatives.
In this research, the total numbers of 300 Malaysian non-financial firms (based on their market capitalization) were selected, from the year 2007 to 2009. Tobin?s Q was used as a measurement of firm value; leverage, firm size, dividend per share, profitability and investment growth were control variables; interest rate derivative, foreign currency derivative and commodity derivatives were dummy variables. Pooled data technique was used in our research.
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ABSTRACT
Over the recent decade, firms increasingly using derivative to hedge their position. The empirical research on the valuation effect derivative has on firm value still remains debated. The purpose of our study is to investigate the effect of using derivative has on firm value in the Malaysia market by using a sample of top 300 non-financial firms in terms of market capitalization from the year 2007 to 2009. Secondary data and quantitative approach were used in our study. The required financial data were collected from companies? annual reports and OSIRIS database. To carry out the analysis, we used ordinary least squares (OLS) and panel data technique to estimate our model. The paper concluded that the usage of derivative could not improve the firm value. We found that commodity and currency derivative was not significantly related to the firm value. Interest rate derivative was partially significant to firm value; however, it was in a negative relationship.
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CHAPTER 1 INTRODUCTION
1.1
Introduction
This chapter provides the overall picture of the research project. It gives an introduction about the background of the research, followed by the problem statements, research questions and research objectives.
1.2
Background of the Study
Derivative is the security whose price is derived from an underlying asset. It serves as a contract between two or more parties on the trading of the underlying asset in the future point of time. In the derivatives market, the most common types of derivatives are future contracts, forward contracts, options and swaps. The main purpose of using derivatives by a firm is to hedge risk. Some may use to speculate and to earn an abnormal profit. According to Nguyen and Faff (2003), firms appeared to use interest rate derivatives to minimize the risk of financial distress. They found that firms used derivatives as a hedge rather than to speculate in the foreign exchange market.
Alkeback, Hagelin and Pramborg (2006) discovered that 59 percent of the non-financial firms in Sweden used derivatives in 2003 compared to 52 percent in 1996, which was a significant increase in derivatives usage among the SMEs. Besides that, the exchange exposure was the most the Swedish firms to manage with, compared to interest rate exposure. In 2003, almost every firm used derivative to manage their foreign exchange exposure and interest rate exposure.
1-1
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Nguyen and Faff (2003) discovered that leverage and firm size were the two most important factors that induced a firm to make use of financial derivatives. However, Carter and Sinkey (1998) did not find the level of participation in the market for interest-rate derivatives was positively related to size. Other than that, El-Masry (2006) argued that larger firms were more likely to use derivatives than medium and smaller firms; public companies were more likely to use derivatives than private firms; and derivatives usage was greatest among international firms. Furthermore, Hentschel and Kothari (2001) examined that financial institutions hold slightly more interest rate derivatives compared with non-financial firms. Raturi (2005) suggested that derivatives were used by larger companies, especially in the life insurance industry.
On the other hand, except for the banks and financial firms, the use of derivatives by non-financial firms has grown rapidly in the last two decades. However, up to present, there is a little consensus regarding what is the effect of the use of derivatives on the market value of the firm (Bartram, Brown & Conrad, 2006). The Modigliani and Miller (1958) paradigm predict that the use of derivatives cannot add value if markets are perfect. However, modern finance theories indicate that there are certain circumstances under which a hedging program using derivatives can be a value enhancing.
Smith and Stulz (1985) argued that hedging could reduce the probability of a firm encountering financial distress by reducing the variance in firm value. For example, banks can use derivatives to reduce the probability of financial distress due to the uncertainty of the fluctuation in interest rate. However, from the finding of Carter and Sinkey (1998), community banks may reject to use derivatives because the cost of implementing a riskmanagement program was higher, such as the start-up costs like hiring trained personnel and development of the internal control systems.
Bartram et al. (2006) examined the effect of derivative use on firm risk and
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value by using a large sample of non-financial firms from 47 countries. They found strong evidence that the use of financial derivatives could reduce both total risk and systematic risk, thus it led to a lower market beta and lower discount rate, therefore a higher firm value. Junior and Laham (2008) also found that the adoption of a hedging policy would increase the firm value.
Other than that, the use of derivatives would be influenced by managers because he was the one who responsible to diversify the risk relating to the firm. Smith and Stultz (1985) investigated that if managers? wealth was in aligning with the firm value, then it was optimal for them to completely hedge the value of the firm.
1.3
Derivatives in Malaysia
In the year of 1980, Malaysia set up the first derivative exchange which was known as Kuala Lumpur Commodities Exchange (KLCE). At the same year, KLCE introduced the first derivative product - Crude Palm Oil (CPO) future contract to the public and it was actively traded in KLCE. Up to present, CPO is still the main derivative product of KLCE, even though KLCE has introduced other commodity future contracts on rubber, tin, cocoa and etc. Although other commodity future contracts are less actively traded compared with CPO, but since they are good substitute contracts traded in foreign exchanges such as Tokyo, London and etc., therefore it would not be taken off from KLCE. Due to the reason that MME was unable to maintain the single contract by itself, it was forced to be merged with KLCE and became a new entity called COMMEX. 1
In addition, the Kuala Lumpur Options and Financial Futures Exchange (KLOFFE) was the first Malaysian financial derivatives exchange which
1
Bacha, O. I., & Merican, O. M. I. (2003). The market for financial derivatives: Removing impediments to growth, 4-5 1-3
The Impact of Derivatives on Firm Value
was established by a consortium of private companies in 1990. It launched the first product - Stock Index Future contract that based on a revamped Kuala Lumpur Composite Index (KLCI) in 1995. After five years later, KLOFFE introduced another product which was index option as its second product. For the KLCI options, it has a vary strike price in call and put option give to investors. However, in early 1999, the owner of KLOFFE sold the financial derivative exchange to the Kuala Lumpur Stock Exchange (KLSE) and become a KLSE?s wholly-owned subsidiary.2
In December 2000, KLOFFE and COMMEX merged together and became Malaysian Derivatives Exchange (MDEX). As a result of merging, MDEX was a single exchange that for all derivatives trading needs to consolidate into this exchange. Due to MDEX was a subsidiary that wholly owned by KLSE, therefore KLSE was a single exchange in Malaysia that provided the trading in stocks as well as both commodity and financial derivatives. After that, KLSE has changed its name to Bursa Malaysia Berhad, therefore MDEX became Bursa Malaysia Derivatives Berhad (BMD). 3
Since the entire derivatives are consolidated in BMD, therefore, now we have commodity, equity and financial derivatives that are ready to be traded in BMD. In total there are nine derivative contracts which are being traded in BMD by today. The nine derivatives contracts are stated at Table 1.1.
2
Deravatif in Malaysia, Retrieved March 06, 2011, from http://www.scribd.com/doc/8246440/deravatif-in-malaysia, 5-6. 3 Deravatif in Malaysia, Retrieved March 06, 2011, from http://www.scribd.com/doc/8246440/deravatif-in-malaysia, 6. 1-4
The Impact of Derivatives on Firm Value
Table 1.1: The Different Types of Derivatives Traded at BMD
Commodity Derivatives
Equity Derivatives
Financial Derivatives
Crude Palm Oil Futures FTSE Bursa Malaysia (FCPO) KLCI Futures (FKLI)
3 Month Kuala Lumpur Interbank Offered Rate Futures (FKB3)
USD Crude Palm Oil Futures (FUPO)
FTSE Bursa Malaysia KLCI Options (OKLI)
3-Year Malaysian Government Securities Futures (FMG3)
Crude Palm Kernel Oil Futures (FPKO)
Single Stock Futures (SSFs)
5-Year Malaysian Government Securities Futures (FMG5)
(Source: Bursa Malaysia, 2011)4
Among the equity derivatives, SSF is the most recent contract (introduced in 2006) that was added in. These futures are based on the individual stocks that listed on Bursa Malaysia and most of them are blue-chip stocks.5 Other than that, FUPO is a crude palm oil futures contract that is denominated in USD, whereas FCPO is denominated in Ringgit, both of them are treated as the worldwide pricing benchmark for palm oil. Bursa Malaysia has enlarged the offering in commodity derivatives that denominated on USD to globalize Malaysian futures market and Bursa Malaysia?s position. As a result, BMD has become the market that is internationally competitive on futures trading.6
4
Derivatives products, Retrieved March 12, 2011 from http://www.bursamalaysia.com/website/bm/derivatives/products/ 5 Single Stock Futures (SSFs), Retrieved March 12, 2011, from http://www.bursamalaysia.com/website/bm/products_and_services/derivative_resources/ downloads/faq_ssf.pdf, 1-2. 6 USD Crude Palm Oil Futures (FUPO), Retrieved March 12, 2011, from http://www.bursamalaysia.com/website/bm/derivatives/products/Commodity_Derivatives/ fupo2.html 1-5
The Impact of Derivatives on Firm Value
1.4
Problem Statement
Over the recent decade, firms increased to use derivative to hedge their position. The derivative market has experienced a rapid growth over the recent year. Even though information on firm derivative usages is widely available, the empirical research regarding whether the use of derivative will increase a firm value is still debatable.
Modigliani and Miller (1958) suggest that firm value will be independent of hedging if perfect capital markets exist (without transaction costs, taxes, bankruptcy cost, agency costs and information asymmetry). The main reason is because rational investors are assumed to diversify their portfolio themselves and therefore there is no value added for a firm to engage in hedging transaction. However, does derivative actually enhancing the firm value in reality? The empirical finding of whether used of derivative for hedging purposes has or has no impact on firm value is still mixed.
Many researchers have conducted empirical work on the impact of using derivative usage on firm value over recent decade. The result of the research is still mixed and therefore we cannot conclude whether hedging has significant impact on firm value. Jorion (1990) found that hedging on foreign currency has no impact on firm value. This result was inconsistent with the finding of Allayannis and Weston (2001). They found that the use of foreign currency derivatives would create value to the firm. Jin and Jorion (2006) investigated the U.S Oil and gas sector and they found an insignificant impact hedging has on firm value. Graham and Rogers (2001) found that hedging would create value to firm by enhancing their debt capacity. A similar research was conducted by Hagelin and Pramborg (2002) in Swedish firms and found that hedging would have a positive effect on firm value.
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The Impact of Derivatives on Firm Value
As a whole, the findings of empirical studies remain controversial; it is not clear whether the decision to use derivatives has an effect on firm valuation. Therefore, this paper extends the literature by testing the hypothesis of whether the use of derivatives is rewarded by a higher market value of a firm, using a sample of Malaysia?s firm.
1.5
Research Questions
This research is important to allow us to examine whether the use of derivatives affects the value of Malaysian non-financial firms. More specifically, we would like to investigate: 1. What is the effect of derivatives use on the firm value? 2. What type of derivatives will have significant impact on firm value? 3. Is the use of derivative can be served as an important indicator to measure the value of the firm?
1.6
Research Objectives
The main objective of this research is to investigate whether the derivatives are positively related to the firm value in Malaysia. As what we have stated in the problem statement, the effect of derivatives usage on firm value is still debatable because the results from various empirical researches show their own interpretation. Therefore this issue becomes our main purpose to conduct this research project. In order to have a deep understanding on the research, we specifically discuss the three main derivatives in the market which are interest rate derivatives, currency derivatives, and commodity derivatives. The objectives are specifically stated in the three forms show in the following.
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The Impact of Derivatives on Firm Value
The first objective is to determine whether the interest rate derivative is positively related to firm value. Interest rate derivative is a form of derivative used to hedge the interest rate risk resulting from the fluctuation of interest rate, and thus affect the financial planning of a company. But how is the effectiveness of hedging interest rate by using the derivative?
The second objective is to find out whether the usage of currency derivative is positively related to firm value. For a multinational enterprise, they always deal with the foreign business partners. Because of this, they are facing the currency risk at all time and hence to use derivative to minimize the risk and losses. Therefore we want to discover if the usage of derivative can really help the firms to minimize the currency risk.
The third objective is to determine whether the use of commodity derivative is positively related to firms? market value. This type of derivative is always used by those companies or manufacturers to hedge the fluctuation of commodity price. For example, Airline industries buy the jetfuel forward contract to lock in the price of fuel at a certain rate in the future point of time.
1.7
Chapter Layout
The research paper consists of five chapters and is organized as follows:
Chapter 1 of this research project first illustrates the background of the research, then toward to explain the problem statements, and the objectives of this research which is going to be conducted. In Chapter 2, we conduct a literature review on the journals and use the findings and results given by these journals to support our research project. Chapter 3 discusses on the sample, key variables, and methodology used to examine the Malaysian firms? valuation reaction to the use of derivatives and. Besides that, we also develop the hypothesis and conceptual
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The Impact of Derivatives on Firm Value
framework for this research project. Chapter 4 discusses about our findings, researched results and we conclude our research project in chapter 5.
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The Impact of Derivatives on Firm Value
CHAPTER 2 LITERATURE REVIEW
2.1
Definition of Derivatives
From the definition of Chance and Brooks (2009), derivative is defined as the financial instruments whose returns are derived from those of other financial instruments. That is, their performance depends on how other financial instruments perform. Derivatives serve a valuable purpose in providing a means of managing financial risk. By using derivatives, companies and individuals can transfer, for a price, any undesired risk to other parties who either have risks that offset or want to assume that risk. There are different types of derivatives such as forward contract, future contract, swap, option, equity derivative, foreign exchange derivative, interest rate derivative and commodity derivative.
2.2
The Use of Derivatives to Hedge Risk
According to a survey from the International Swaps and Derivatives Association7, there were 94% of the world?s 500 largest companies in 2009 used the derivatives to manage and hedge their business and financial risks. The survey found that foreign exchange derivatives were the most widely used instruments which were 88 percent, followed by interest rate derivatives (83 percent) and commodity derivatives.
7
International swaps and derivatives association, News release April 12, 2009. Retrieved March 10, 2010, from http://www.isda.org/press/press042309der.pdf 2-1
The Impact of Derivatives on Firm Value
From the article of David Harper (2010)8, he mentioned the uses and the functions performed by derivatives are as follow: ? Foreign Exchange Risk: The risk that changes in the currency exchange rate will have an adverse effect on the company?s revenue. It also known as currency risk. ? Interest Rate Risk: Companies can hedge interest-rate risk in various ways. Consider a company wishes to sell a division in one year but the interest rate is expected to fall in the future, then it could purchase (or 'take a long position on') a Treasury futures contract to lock in the interest rate by today. Thus, the company is effectively locking in the future interest rate. ? Commodity or Product Input Hedge: This is the risk commonly faced by companies that are heavily sensitive to the price change of raw-material inputs or commodities. For example airline industry, it consumes lots of jet fuel. In the past, most airlines have given a great deal of consideration to hedging against crude-oil price increases.
2.3 Research Theory
2.3.1 Interest Rate Derivatives
Interest rate derivatives are instruments whose payoffs are dependent in some way on the level of interest rates. In the 1980s and 1990s, the volume of trading in interest rate derivatives in both the over-the-counter and exchange-traded markets increased very quickly. Many new products were developed to meet particular needs of end-users. The key challenges
8
Harper, D. (2010). How companies use derivatives to hedge risk. Retrieved March 10, 2010, from http://www.investopedia.com/articles/stocks/04/122204.asp 2-2
The Impact of Derivatives on Firm Value
for derivatives traders are to find good, robust procedures for pricing and hedging these products.9
There are different types of interest rate derivatives, one of these is interest rate cap. It can be characterized as a portfolio of put options on zero-coupon bonds with payoffs on the puts occurring at the time they are calculated. Analogously to an interest rate cap, an interest rate floor is a portfolio of put options on interest rates or a portfolio of call options on zero-coupon bonds.10
Swap options, are options on interest rate swaps and are another increasingly popular type of interest rate option. They give the holder the right to enter into a certain interest rate swap at a certain time in the future. Many large financial institutions that offer interest rate swap contracts to their corporate clients are also preparing to sell swap options to them or buy swap options from them. 11
2.3.2 Foreign Currency Derivatives
Firms in the plantation, industrial product, trading services, and consumer products manufacturing sectors are the main users of the foreign currency derivative (FCD) in Malaysia. It is a type of contract that derives the value from an underlying asset such as currency or exchange rate. Allayannis and Weston (2001) discovered that firm would have higher value by using currency derivatives in its risk management operation. In order to mitigate the impact of foreign exchange rate fluctuations, it has been claimed that firms could employ financial hedge strategies through foreign currency derivatives (Chiang & Lin, 2005). Since there are many investment tools
9
Hull, J.C. (2006). Options, Futures, and Other Derivatives, Seventh Edition. Pearson/Prentice Hall. Page 639 10 Hull, J.C. (2006). Options, Futures, and Other Derivatives, Seventh Edition. Pearson/Prentice Hall. Page 644 11 Hull, J.C. (2006). Options, Futures, and Other Derivatives, Seventh Edition. Pearson/Prentice Hall. Page 650 2-3
The Impact of Derivatives on Firm Value
are in high risk, in order to prevent unexpected losses in the future, investos tend to use foreign currency derivative to minimize the risk they are facing now such as foreign currency risk. Similar with the finding of Makar and Huffman (2008), they reported that US foreign-denominated debt issuers used foreign currency derivatives to hedge short-term risk effectively. Besides it also increased their firm value by not losing money on the premium paid out.
Bartram, Brown and Fehle (2006) found evidence that those firms have foreign currency transaction tend to use foreign currency derivatives. Foreign currency transaction normally comes with foreign currency risk. For the speculator, their motivation of using derivative is to earn an abnormal profit, so they intend to use FCD to speculate rather than to hedge, since this kind of derivative instrument is the marginal product that only needs minimum amount of initial capital and ends up to gain a huge profit. It is similar with the finding of Anand and Kaushik (2008) in which speculation was the objective of using foreign currency derivatives.
2.3.3 Commodity Derivatives
A commodity derivative is a derivative contact in which a commodity is the underlying asset. Commodity derivatives are the financial instruments that derive the value from the value of the underlying commodity in order to achieve price risk management (Lokare, 2007). It is necessary to understand the reason why commodity derivatives are important and also the role they can play in risk management. Because of the price of commodities, metals, shares and currencies fluctuate over time, the possibility of adverse price changes in the future creates risk for businesses. And hence derivatives are used by firms to reduce or eliminate price risk arising from unforeseen price changes (Ahuja, 2006).
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The Impact of Derivatives on Firm Value
Commodity derivatives are not new. In pre-Christian civilizations, forwards on agricultural products have already existed. Forwards are defined as contracts between two parties to deliver a certain product at an agreed price on the future certain date. On the other hand, futures are the standardized forwards that freely exchangeable on the market in which first appeared in Chicago in the 1840. Because the existence of exchanges that appeared to facilitate the matching of buyers and sellers of contracts, thereby lead to increase the liquidity of derivative markets. The historical role of commodity derivatives is that to hedge against inherent risks existing in commodity markets (Cinquegrana, 2008). The commodity derivatives trading in India has its long history. In today?s India, there are large numbers of agricultural commodity contracts are traded on the exchanges. The value of agricultural commodities traded as a proportion of overall GDP amounts to around 37 percent (70 percent of the agricultural GDP) in the country compared with the share of billion, oil and other metals is relatively low (Lokare, 2007).
2.4 Empirical Discussion
2.4.1 Interest Rate Derivatives
In the past few decades, the use of interest rate derivatives has grown substantially. Interest rate risk represents the most significant source of market risk for many lodging firms. Much of this exposure is from floatingrate bank loans because changes in interest rates can increase cash flow and earnings volatility in an uncertain interest rate environment. Higher interest rates can also make it more costly for firms to raise external financing. By matching the exposure of assets with the exposure of debt, managers can ensure that the supply of funds from operations and/or debt financing will match the demand for funds for its capital investment opportunities and reduce the need for costly external financing (Froot, Scharfstein & Stein, 1993). However, the recent research has questioned
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The Impact of Derivatives on Firm Value
their importance and their efficacy in the risk management toolbox of nonfinancial firms. Guay and Kothari (2000) argued that the effect of derivative use was too small; whereas Faulkender (2005) showed that the firms in the chemicals industry tend to use interest rate derivatives to speculate rather than to hedge.
Singh (2009) conducted a research to investigate the relationship between the interest rate derivative positions, debt maturity structure, and exposure for a sample of lodging firms, gaming firms, and lodging REITs, for the period from 2000 to 2004. The results showed that lodging firms were positively exposed to interest rate risk. Interest rate derivatives such as interest rate swaps and caps were used in conjunction with debt maturity structure to mitigate interest rate exposure and to lower borrowing costs. By issuing floating debt and swapping into fixed-rate debt, smaller unrated firms would realize benefits from lower financing costs, lower costs of financial distress, and lower interest rate exposure. On the other hand, firms with high debt ratings were more likely to issue fixed-rate debt and swap into floating-rate debt. In addition, the results supported the conclusion that the yield spread has a positive and significant effect on swap usage.
Covitz and Sharpe (2005) discovered that smaller firms have more exposure on interest rate from their liabilities compare to the larger firms. Thus, smaller firm will tend to use the derivative to neutralize the interest rate exposures. For the larger firms, they will use their choice of debt structure to limit their interest rate exposures rather than with derivatives.
Batram et al. (2006) examined whether derivatives use was associated with higher firm value on a sample of 7263 non-financial firms from 48 countries. In order to test the relationship between derivatives use and firm-specific as well as country-specific factors, two types of models were estimated. The first was a single-equation PROBIT model using the full sample of general derivatives. The second was a trivariate PROBIT model
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The Impact of Derivatives on Firm Value
with separate equations for FX, IR, and CP derivatives. They found that only the firm that using interest rate derivatives has a positive valuation effect.
Nelson, Moffitt, and Graves (2005) examined with the samples of 5700 non-financial firms and their use of currency, interest rate, and commodity derivatives. Tobin?s Q as a proxy for firm value, they looked directly at the stock return performance of firms that disclosed the use of derivatives for the purpose of hedging. In the research they found that there was a negative effect of interest rate derivatives on firm value. Nguyen and Fatt (2007) addressed the question of whether the use of financial derivatives among a cross section of Australian firms delivered a positive increment in firm value. In doing so, they investigated both the relationship between an aggregate measure of derivatives and firm value as well as the impact that individual types of derivatives potentially have on firm market value, as proxied by Tobin?s Q. The result showed that there was a negative relationship between derivatives use and firm value. Rather, their result strongly indicated that the use of derivatives in general and the use of interest rate derivatives in particular lead to a reduction in firm value or a „derivative user? discount.
Ameer (2009) examined the state of risk management practices among Malaysian listed firms and evaluated the value-relevance of the notional amount of foreign-exchange (FCD) and interest-rate derivatives used by listed firms over the period 2003-2007. He applied the linear regression framework into his research and found that only a few firms hedge the market risks in Malaysia. The main users of the FCDs in Malaysia are the firm in the plantation, industrial product, trading services and consumer products manufacturing sectors. In addition, the total earning and the use of derivatives have a significant positive correlation. This findings showed that its contribution to a the valuation of firms was very minimal in Malaysia than other countries although there have a value-relevance by a disclosed notional amount of the derivatives
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The Impact of Derivatives on Firm Value
2.4.2 Foreign Currency Derivatives
Allayannis, Lel and Miller (2009) examined how corporate governance impacts firm value through hedging. They used foreign currency derivatives associated with a higher valuation for firms that have strong internal or external corporate governance. The data was collected from thirty-nine countries between 1990 and 1999 that were cross-listed in the U.S. as level II and level III ADRs, they split the country differences into internal (firm-level) as well as external (country-level) corporate
governance structures. The researcher used the market-to-book ratio as a proxy for Tobin?s Q to reflect a firm?s market value. They concluded that hedging premium only for firms that have strong internal and external corporate governance, while there was no hedging premium for firms with weak corporate governance. With strong internal and external, foreign currency derivatives added value to the market firm value or vice versa.
Allayannis and Weston (2001) investigated the impact of using foreign currency derivative has on the firm value. They used 720 largest U.S. nonfinancial firms between 1990 and 1995 as a sample and used Tobin?s Q as an approximation for firm?s market value and robustness tests. They also measured the market-to-book ratio (simple Q) and the market-to-sales ratio. Their results concluded that foreign currency derivative was positively and significantly correlated with the firm value. The researcher also found that the firm value would be increased and if they performed hedging activities and vice versa.
Nguyen and Faff (2003) reexamined on an empirical exploration of the motives behind the aggregate use of financial derivatives- foreign currency and interest rate derivatives by Australian companies. This journal data contained sample of non-financial Australian companies- 469 firms from 1999 and 2000 from the Connect database. Logit and Tobit regression and also the LR (likelihood ratio) statistic tests were used to analyze the result. The result showed that foreign currency derivative appeared to be cost2-8
The Impact of Derivatives on Firm Value
based and related to the issuance of foreign-currency-denominated debt. The use of FCD was strongly linked to value-enhancing motives.
Capstaff, Marshall and Hutton (2007) investigated the use of FCD by French firms before and after the introduction of the euro. The purpose was to examine if the introduction of euro currency on financial practices would actually reduced the currency risk, and hence reduced the motive of using foreign currency derivative to hedge the risk. Samples of 120 French firms were collected across the periods before and after the introduction of the euro 1996 and 2000. Various types of method were used to test the result, such as F-statistic, Jarque–Bera (J–B), Ryan Joiner statistics, the White?s test, Berry and Feldman graphical technique and also DFFITS test. As a result, after the adoption of the euro, the level of exposure to foreign currency risk decreased, hence lead to a decrease in the level of foreign currency derivative usage.
Allayannis and Ofek (1997) examined the purpose of using foreign currency derivatives. The total of 500 non-financial firms was selected as the sample. The researcher found that there was a strong negative association between foreign currency derivative use and firm exchangerate exposure, the meaning is that firms used derivatives to hedge rather than to speculate in the foreign exchange markets. A firm's exposure to exchange-rate movements was mitigated through the use of foreign currency derivatives.
Makar and Huffman (2008) examined the relationship between UK multinationals? stock returns and changes in the principal exchange rate. They also investigated whether the firms effectively used foreign currency derivatives and foreign-denominated debt to lower the currency risk associated with the bilateral exchange rate to which they were more likely to expose with. The sample consisted of 44 firms UK multinationals listed in the June 2001 FTSE 250 that operated in the non-financial sector, for the 1999–2002 sample periods. They used OLS Regression, the Shapiro –
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The Impact of Derivatives on Firm Value
Wilk test for non-normality, and the White test for heteroskedasticity and also hypothesis tests. The result indicated that the currency risk could be effectively hedged by the financial currency-hedge techniques.
Hentschel and Kothari (2001) conducted a research to investigate whether the use of derivatives allowed firms to reduce their level of riskiness. A total number of 325 non-financial firms and 100 financial firms were selected as the sample. They used Tobin?s Q, univariate test and multivariate test to test their result. Their result indicated that there was no significant relationship between the volatility of a firm?s stock prices and the size of the firm?s derivatives position.
Magee (2009) investigated the effect of foreign currency hedging with derivatives on firm value in a dynamic panel framework by using the system generalized method of moments (GMM) estimator. By using the system GMM estimator, it allows the researcher to control for unobserved firm specific factors, persistence in firm value and feedback from the past amounts of firm value to the current amount of foreign currency hedging. The sample consisted of 408 large U.S. non-financial firms with foreign sales from operation abroad during the period of 1996 to 2000 which was measured by Tobin?s Q. The result showed that the foreign currency hedging would increase firm value when foreign currency hedging was assumed to be strictly exogenous. However, the researcher also found that the use of foreign currency derivatives no longer affect the firm value.
2.4.3 Commodity Derivatives
Commodity derivatives markets have witnessed tremendous growth in recent years. Chang, Hong and Kuan (2005) examined the impact of hedging activities of Canadian oil and gas companies on their stock return and firm value for the period of 2000-2002. The impact of hedging on firm value was measured by Tobin's Q ratio by using both linear and nonlinear
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The Impact of Derivatives on Firm Value
models. They found that the large Canadian oil and gas firms were able to hedge against the downside risk induced by unfavorable oil and gas price changes. However, gas hedging appeared to be more effective than oil hedging when downside risk presented. Therefore, hedging for gas (together with profitability, leverage and reserves) has a significant impact on firm value. Bartram et al. (2006) did a survey on the effect of derivative use on firms? risk measures and value. The derivative use was more prevalent in firms with higher exposures to interest rate risk, exchange rate risk and commodity prices. They did the research by using a large sample of 6,888 non-financial firms from 47 countries. They found strong evidence that the use of financial derivatives reduced both total risk and systematic risk and there was a positive relationship of derivative use on firm value but the effect was not strong.
Carter, Rogers and Simkins (2002) examined a sample of firms in which hedging positions could achieve economically significant objectives. They investigated jet fuel hedging behavior of firms in US airline industry during 1994-2000 to examine whether such hedging is a source of value for these companies. The result showed that jet fuel hedging was positively related to airline future purchases of jet fuel. They found evidence to support view that airlines, on average, increased firm value by using derivatives to hedge against changes in jet fuel prices.
However, Jin and Jorion (2006) examined the hedging activities of a sample of 119 U.S. oil and gas produce from 1998 to 2001 with the measurement of Q ratios, it showed that hedging did not affect the market value and there was no difference in firm values between firms that hedged and firms that did not hedge.
From the research of Hentschel and Kothari (2001) using data from ?nancial statements of 425 large U.S. corporations, they investigated
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The Impact of Derivatives on Firm Value
whether ?rms systematically reduce or increase their riskiness with derivatives. They found that many of the largest U.S. corporations were active participants in derivatives markets and manage their exposures with large derivatives positions. Firms with derivatives hold similar notional principals of foreign exchange and interest rate derivatives but they hold almost no commodity derivatives. Non-?nancial ?rms hold slightly more foreign exchange derivatives, while ?nancial institutions hold slightly more interest rate derivatives. In the research, they found out that there was no association between the volatility of a ?rm?s stock prices and the size of the ?rm?s derivatives position. Moreover, a ?rm?s exposures to variations in interest and exchange rates were not directly related to the ?rm?s derivatives position.
Nelson et al. (2005) examined the annual stock performance of 1,308 U.S. firms over the period per year 1995-1999. They found that firms that hedged outperform other securities by 4.3 percent per year on average. They pointed out that the over performance was entirely due to larger firms that hedged currency. However, they discovered that there were no abnormal returns for firms to hedge either with interest rate or commodity derivatives.
2.4.4 Firm Size
Cohen, Levin, and Mowery (1987) found that there was no significant relationship between size and R & D intensity once care is taken to separate the influence of business unit and firm size. Therefore, we might have to take into account any other factors to get accurate point.
Mak and Kusnadi (2005) examined the impact of corporate governance mechanisms on the firm value of Singapore and Malaysia firms. The sample included 271 firms listed on the SGX and 279 firms listed on the KLSE, financial data, board composition, ownership structure, and other
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The Impact of Derivatives on Firm Value
relevant data for each firm for the 1999 or 2000 financial years. They used Tobin?s Q and multivariate tests as measurement. The result showed that there was an inverse relationship between board size and firm value in both countries.
Ushijima (2003) investigated the evaluation of corporate multinational and its effect on the stock market valuation of the firm. The sample was balanced panel of manufacturing firm continually listed on Tokyo Stock Exchange from 1985 to 1995, total of 5124 firm-year observations. This project was measured by simple proxy of Tobin?s Q. The result showed that firm size which was a central screw to the multinational company and multiplier value for the company was not value negative with itself, in fact the value of multinational firm increase with its firm size, which presumably, monitoring problem would be worse, could not be recovered by theory.
2.4.5 Leverage
Before a firm undertakes a project, it must have sufficient funds with itself. Normally, a big firm will borrow loan from bank or issue bond to raise funds, then it only can increase their potential returns. However, at the same time the companies? debt will increase as well. Leverage is calculated by the amount of debt that uses to finance firm?s assets. Firms that have more debts than assets are considered as high leverage firm. Investor usually will advert to the high leverage firms because there are high possibilities that the firm may not be able to repay the debt. According to Ward and Price (2006), financial leverage was the proportion of capital, the greater the level of debt, the higher the leverage. According to Modigliani and Miller?s (1958), return on equity should be increased if the firm?s level of debt increases. Besides, Ward and Price (2006) indicated that if there was an increase in debt-equity ratio,
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The Impact of Derivatives on Firm Value
shareholder returns would raise. However, Rajan and Zingales (1995) argued that there was a negative relationship between debt and profitability.
Iturriaga and Crisostomo (2010) examined the effect of leverage, dividend payout, and ownership concentration on firm value with or without growth opportunities. A total of 213 samples from Brazilian firms were collected between 1995 and 2004. They used Generalized Method of Moments (GMM), Hansen Test and Arellano-Bond to test the results. The result showed that leverage has a dual effect on the value of the firm, which was negative for firms with growth opportunities and positive for firms without growth opportunities. Rayan (2008) examined whether the firms? financi al leverage was positively or negatively related to firm value in a South African context. The data that they used in their research was secondary data, which was sourced from Mcgregor BFA database for the period 1998-2007. 113 Johannesburg Stock Exchange (JSE) listed firm were included, which were stratified by industry. The method used was regression analysis. The result showed that there was a negative relationship between firm value and firms leverage.
Salehi and Biglar (2009) examined whether the capital structure decision would have an impact on firms? performance. They applied the data of 117 corporate in Tehran Stock Exchange (TSE) in a 5-year time horizon (20022007). Descriptive statistics containing mean, standard deviation and inferential statistics containing Pearson Correlation, and ANOVA test were used in their research. The result showed that firm value was negatively related to the firm?s financial leverage.
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2.4.6 Investment Growth Previous literatures have tried to examine the impact of the firm?s long term capital expenditure or spending decision on its market value. Fama and Jensen (1985) stated that during the efficient market, if the managers decide to choose the investment project with positive NPV value, the firm value and shareholders wealth thus can be maximized and market reaction should be positively for any announcement of a new investment decisions by a firm.
Ehie and Kingsley (2010) investigated the relationship between the investments in R&D and market value among the firms by using a sample of 26,499 US firms over the period of 1990 to 2007. After they controlled the firm and market-related factors, they found out that R&D expenditures gave persistent positive effect on market value for both manufacturing and service firms.
Bajo,
Bigelli
and
Sandri
(1998)
studied
the
new
investment
announcements by Italian firms listed on the Milan Stock Exchange in a period of 1989-1995. They found that there was a positive relationship between stock price and new investment decisions. In additions, stock price responded better for joint venture announcements and for non-state owned companies.
Chung, Wright and Charoenwong (1998) examined the effect of corporate capital expenditure decisions on share prices. They collected the data on capital expenditure announcements from US companies using Nexis/Lexis services over the 15 year period (1981-1995). By using the certain sample selection criteria, they gathered 308 capital expenditure announcements and computed the Tobin?s Q for each compa ny, and then they separated the company into high Tobin?s Q group and low Tobin?s Q group. According to previous studies, firms with high Tobin?s Q ratio were expected to have positive NPV projects and vice versa, thus increased in
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The Impact of Derivatives on Firm Value
capital expenditures of those firm were expected to be positively accepted by the market and hence increased in share price and vice versa. However, the firms with low Tobin?s Q ratios were perceived as having a lack of valuable or low profitable investment opportunities. Market reactions generally were less positive toward the announcements of capital expenditure increase, but tend to view favorably if it reduced capital expenditures. They discovered that market did respond strongly to good decisions when there was an increase of capital expenditures by the firms with high Tobin?s Q and vice versa. However, the decision to decrease (increase) the capital spending by the firms with high Tobin?s Q (low?s Q firm) did not have significant negative impact on market reactions. They concluded that firm?s growth prospects determined the market?s reaction to their capital expenditure decisions.
2.4.7 Dividend Per Share
Miller and Modigliani's (1961) irrelevance theorems proposed that relationship between dividend policy and firm?s val ue is independent under certain assumptions such as perfect capital market and in the absence of taxes, bankruptcy costs, and asymmetric information. The distribution of cash dividend to shareholders was believed that should not have any impact on a firm?s stock prices. Lastly, the Miller an d Modigliani concluded that firm?s value could only be affected by firm?s investment policy alone which generated future cash flow based on the investment undertaken and not influenced by the manner in which its cash flows were split between dividend and retained earnings. “Dividend signaling hypothesis” was initially mentioned in Lintner (1956) paper, and further enhanced by Fama, Fisher, Jensen, and Roll (1969) and Ambarish, John, and Williams (1987). They believed that manager could distribute dividend to signal asymmetric information about the firm?s
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The Impact of Derivatives on Firm Value
future growth prospects, because manager was believed to have reliable private information about the firm future financial position and could signal those private information to investor through dividend distributions. Market generally believed that dividend change announcement would convey valuable information regarding the firm future growth prospects and earnings. Therefore, an announcement of a dividend increasing or decreasing was followed by an increase or decrease of stock prices subsequently.
Lang and Litzenberger (1989) suggested that free cash flow hypothesis explaining stock price reaction to dividend change announcements. Significant stock price behavior (increase in stock price) could occur when investors expected that the increase of dividend could limit the cash flow available for the firm?s managers to invest in the negative NPV or wasteful projects, whereas investors expected that announcements of decrease of dividend may signal that firm?s overinvesting policy and thus decrease of stock prices subsequently.
Azhagaiah and Priya (2008) examined the relationship between the shareholders? wealth and dividend policy on Organic and Inorganic Chemical Companies in India over the period of 1997 to 2006. During that period, any companies paid dividend for 3 years or more were treated as dividend paying company, otherwise was served as a non-paying company. The result indicated that there was a significant difference in average market value relative to book value of equity between dividend companies and non-dividend companies of both organic and inorganic chemical companies. They concluded that generally higher dividend did increase the market value of the firm and vice versa.
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The Impact of Derivatives on Firm Value
2.4.8 Profitability Modigliani and Miller (1958) stated that a firm?s value could be maximized by using more debt in its capital structure; debt would help the firm to decrease their average cost of capital and enhance profitability as long as its ROA was greater than the before-tax interest paid on debt. ROE was found to be insignificant in determining the firm value.
Hall and Brummer (1999) determined which internal performance measures of a company correlate the best with its external performance measures as represented by the Market value added (MVA) of the corporation. MVA is the external method that used to determine the wealth of shareholder while for the internal measures of shareholder value creation is Economic value added (EVA) and other variable or ratios. As a result, they found out that there was a positive correlation coefficient between MVA and discounted EVA when inflation adjustments to the data had been made. Besides, there were slightly lower positive correlations were obtained between MVA and more traditional accounting-based corporate performance measures such as return on assets (ROA), return on equity (ROE), earnings per share (EPS) and dividends per share (DPS).
Mir and Nishat (2004) examined the link between corporate governance structure and the firm performance in Pakistan by using weighted least square regression techniques. The sample consisted of 248 firms randomly selected from the listed companies during 2003. The parameters of corporate governance were related to management, shareholders or stakeholders and board of directors, etc. While return on asset (ROA), Tobin?s Q and stock return were included in performance parameter. The result showed that there was positive impact on firm performance by corporate governance structure variables such as percentage block holding by individuals and family members and by industrial companies. However, the percentage of block holding by insider has negative signal
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The Impact of Derivatives on Firm Value
on firm performance. If CEO acts as chairperson of board of directors, the firm performance will be affected negatively. There was no impact on firm performance shown by the composition of board. Furthermore, the firm size has a positive impact on the performance of firm but the expected leverage has a negative relationship with performance.
Ukenna, Ijeoma, Anionwu, and Olise (2010) studied on the relationship between the human capital in a company and the firm?s performance. Their research objective was to find out to what extend the investment on human capital of a company will impact on its overall performance. Second, they wished to discover the perception of a small company regarding to the relationship between human capitals investment and the firm?s performance. They used a sample of twenty five small scale business in Nigeria with the criteria of the amount of staff was less than six and its capital base was not more than hundred thousand naira. The business owners were drawn from bookshops, supermarkets, business centers, computer schools, and sellers of computer accessories. The result showed that there was a strong relationship between the human capital effectiveness and financial performance of a small scale firm.
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The Impact of Derivatives on Firm Value
CHAPTER 3 RESEARCH METHODOLOGY
3.1
Introduction
This chapter outlined the research design, described the sample population and sampling procedures and methods used for data collection. The variables and formulas used in this study were shown and the data analysis technique used will be explained.
3.2
Research Design
The study was aimed at examining the valuation effect of derivatives used in Malaysia market using a sample of 300 non-financial firms over the period 2007-2009. The research adopted quantitative approach and secondary data were used for this study. The approach taken was the application of linear regression framework and panel data technique.
3.3
Data Collection Method
Sample companies were selected based on their market capitalization. The sample in this study comprised the top 300 non-financial firms in terms of market capitalization. The required financial data were collected from OSIRIS database and annual reports of companies over the years 2007-2009. Firms were classified as derivative user or non-user of derivatives based on a search from their annual reports for information about the use of derivatives. We used a dummy variable that was set to one for firms that use any types of derivatives and zero for non-user firms.
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The Impact of Derivatives on Firm Value
The aggregate use of financial derivative was separated into three subsets which are foreign currency derivative, interest rate derivative and commodity derivative. Dummy variable was assigned to each type of derivatives.
3.4
3.4.1
Variables Specification
Dependent Variable
Market values of the firm will be the dependent variable and it was proxy by Tobin?s Q. We adopted the formula approximate q developed by Chung and Pruitt (1994); where the approximate q was calculated by using market value of firm value plus preferred share plus debt and then divided by book value of the total assets; where debt was the value of the firm?s short-term liabilities minus short-assets plus book value of the firm?s long term debt.
3.4.2 Independent Variables
There are three independent variables which included foreign currency derivatives, interest rate derivatives and commodity derivatives. We assigned a dummy variable that was set to zero for firms that do not use derivatives and one for firm that use derivatives.
3.4.3 Control Variables
We included the following control variables, as in Allayannis and Weston (2001). The set of control variables in Tobin?s Q regression included factors known to explain the cross-section of firm value. These factors included:
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The Impact of Derivatives on Firm Value
i.
Size. The logarithm of total assets was used to control for firm size. Even though the relationship between firm value and firm size remained mixed, but we controlled the firm size for two reasons. According to Allayannis and Weston (2001), they found differences in Tobin?s Q for small firm compared to larger firm where small firms were associated with higher Tobin?s Q. But, on t he other hand, Bodnar, Marston and Hayt (1998) 12 found that large firms were more likely to hedge than small firms.
ii.
Leverage. Leverage was proxy by the ratio of long-term debt to the market value of firm. According to Fama and French (1998) and Allayannis and Weston (2001), they found a negative relationship between leverage and firm value.
iii.
Profitability. Profitability was considered as a key value driver. We used the return on assets and return on equity to control for profitability.
iv.
Investment growth. Investment opportunity is proxy by CAPEX (the ratio of capital expenditures to market value of firm). According to Myers (1976), future investment opportunities will have an impact on firm value. Hedgers may have larger investment opportunities, thus it is important to control the variable.
v.
Dividend per share. We controlled for dividends by using dividend per share rather than dummy variable. According to the study conducted by Fama and French (1998), they found that dividends announcement will convey information about future profitability.
Finally we excluded the variables, industrial and geographic diversification, that appeared in Allayannis and Weston (2001).
12
Bodnar, G. M., Marston, R. C., & Hayt, G. (1998). 1998 Survey of financial risk management by U.S. non-financial firms. Wharton/CIBC World Markets 1998 Financial Risk Management Survey: Executive Summary. 3-3
The Impact of Derivatives on Firm Value
3.5
Data Analysis Technique
3.5.1 Tobin’s Q The firm?s market value was calculated by using the formula of approximate q (Chung and Pruitt, 1994) 13 . We adopted the formula approximate q developed by Chung and Pruitt (1994), as the
measurement of the firm market value in our research. They created a simple formula to approximate the Tobin?s q of Lindenberg and Ross (1981)14 where the formula involved relatively easy calculation compared to the L-R?s Tobin?s q and required only basic accounting data that can be easily collected from financial statement of the firms. A very high correlation between the Lindenberg-Ross?s Tobin?s q and approximate q have been observed. They found that at least 96.6 percent of the variability of Tobin?s q was explained by approximate q. The primary difference between L-R and approximate Tobin?s q is that the latter assumed that the replacement values of a firm?s plant, equipment and inventories equal to their book value. The formula was defined as:
Approximate q= (MVE+PS+DEBT)/TA MVE = product of a firm?s share price and the number of common stock shares outstanding PS = liquidating value of the firm?s outstanding preferred stock DEBT = short-term liabilities - short-term assets + book value of long term debt TA = book value of the total assets of the firm
In using the formula to calculate q value, we might get a negative value. Some of the firms did not use long term debt to finance their business and
13
Chung, K. H. & Pruitt., S. W. (1994). A simple approximation of Tobin?s q, financial management, 23(3),70-74 14 Lindenberg, E. B., & Ross, S. A. (1981). Tobin?s q ratio and industrial organization. Journal of Business, 1-32 3-4
The Impact of Derivatives on Firm Value
they have more short term assets than short term liabilities; this has resulted in a negative debt value. When this negative debt value is too big and overweighs the market value of firm and preferred shares, the q value will turn out to be a negative value.
3.5.2 Multivariate Analysis
From the empirical research of Khediri (2010), he developed the multivariate analysis and estimated a specification for the regression models to investigate whether derivatives use are valued at a premium. He estimated the following equations: Tobin?s Qit = ? + ? (derivatives use decision) + ?? j (control variable j) + µi + ?it Where: Tobin?s Q = Market value of the firm and measure how much v alue is created for given amount of assets. Derivatives = Dummy variable equal to 1 for firm using derivatives, otherwise 0 Derivatives use extent = Firm?s outstanding notional amount of derivatives scaled by firm size ? = Constant ? = Estimated coefficient for corporate hedging proxies. ? = Estimated coefficient for control variables. µi = Individual effect of firm. ?it = Error term.
Since our research objectives are similar with that objectives founded in Khediri?s research, thus we adopted the formula used by Khediri?s .
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The Impact of Derivatives on Firm Value
Our multivariate analysis is as below: Tobin?s Q = ?1 + ?2 DUMINT + ?3 DUMCOM + ?4 DUMCUR + ?5 SIZE + ?6 LEV + ?7 ROA + ?8 ROE + ?9 INVG + ?10 DPS ?1 ?2 DUMINT
= Constant = 1 if firm using interest rate derivative and 0 otherwise
?3 DUMCOM ?4 DUMCUR ?5 SIZE ?6 LEV
= 1 if firm using commodity derivative and 0 otherwise = 1 if firm using currency derivative and 0 otherwise = Log of total assets = Leverage; calculated by total debt divided by total equity = Return on asset; calculated by net income divided by total assets = Return on equity; calculated by net income divided by shareholders? equities = Investment growth; calculated by capital expenditure divided by market value of firm = Dividend per share
?7 ROA ?8 ROE ?9 INVG ?10 DPS
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The Impact of Derivatives on Firm Value
Figure 3.1: Conceptual Framework
Interest Rate Derivatives
Foreign Currency Derivatives
Commodity Derivatives
Size
Leverage
Firm Value
Profitability
Investment Growth
Dividends per share
3.5.3
White
Heteroskedasticity-Consistent
Standard
Error
and
Covariance
Heteroskedasticity-consistent standard errors and covariance has been used to deal with the problem of heteroskedasticity by producing more normally-distributed standard errors.
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The Impact of Derivatives on Firm Value
3.5.4 Panel Data Techniques
Panel data, also called longitudinal data or cross sectional time series data, are data where multiple cases were observed at two or more time periods. In this study, panel data technique is used and different empirical models are considered. Most other studies assume is used and different empirical models are considered. Most other studies assume that the unobservable individual effect is zero and use a pooling regression to estimate the Tobin?s Q equation. The assumption of zero unobservable individual effect is too strong that there is large heterogeneity across firms. To control for individual firms heterogeneity, we employ a random effect as well as fixed effect model.
-FIXED EFFECT MODEL
Fixed effects model is the model to use when you want to control for omitted variables that differ between cases but are constant over time. It lets you use the changes in the variables over time to estimate the effects of the independent variables on your dependent variable, and is the main technique used for analysis of panel data. There are five assumptions under this model: i. Assumed that intercept and slopes are the same over time and individuals and the error term captures over time and individuals. ii. Assumed the slope coefficients are constant but the intercept varies over individuals. iii. Assumed the slope coefficients are constant but the intercept varies over individual and time. iv. v. Assumed that all coefficients vary over individuals. Assumed the intercept and coefficients vary over individual and time.
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The Impact of Derivatives on Firm Value
The model is adequate if we want to draw inferences only about the examined individuals. Yi,t = ?i + xi,t? + ei,t Yi,t = dependent variable ?i = unobserved random variable characterizing each unit of observation xi,t = vector of observable random variables ? = vector of parameter of interest
ei,t = stochastic error uncorrelated with x
-RANDOM EFFECT MODEL
The random effect model is the model to use when there are some omitted variables may be constant over time but vary between cases, or there are some omitted variables that may be fixed between cases but vary over time.
The key assumption under this model is there are unique, time constant attributes of individuals that are the results of random variation and do not correlate with the individual regressors. This model is adequate, if we want to draw inferences about the whole population, not only the examined sample. If the cross section data are “drawn” from a large population, they may not act in a similar way with respect to the independent variable.
Start with basic model
Yit ? ?1i ? ? 2 X 2it ? ? 3 X 3it ? uit
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The Impact of Derivatives on Firm Value
Instead of treating ? 1 as fixed, we assume that it is a random variable with a mean value of ? 1 , and the intercept value for an individual company can be expressed as
?1i ? ?1 ? ?i
Where of
i ?1 ,2,...,50
?i
is a random error term with a mean value of zero and variance
? e2
Yit ? ?1 ? ? 2 X 2it ? ?3 X 3it ? ? i ? uit
Yit ? ?1 ? ? 2 X 2it ? ? 3 X 3it ? wit
The composite error term wit consists of two components,
?i which is the
cross section, or individual-specific, error component, and u it , which and is the combined times series and cross section error component. In ECM (random effect model), the intercept ? 1 represents the mean value of the entire cross sectional intercepts and the error component
?i
represents the (random) deviation of individual intercept from this mean value.
3.5.5 Hausman Specification Test
Hausman
specification
test
(Hausman,
1978)
was conducted
to
statistically test which empirical model is most suitable for estimating Tobin?s Q equation. The test evaluated the significance of an estimator versus an alternative estimator. It helped one evaluate if a statistical model corresponds to the data.
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The Impact of Derivatives on Firm Value
3.6
3.6.1
Hypotheses Development
Interest Rate Derivatives
Singh (2009) found that lodging firms were positively exposed to interest rate risk. According to him, smaller unrated firms tend to benefits from lower cost of financing, financial distress and interest rate exposure if a firm issue floating debt and swapping into fixed-rate debt. By contrast, firms with high debt ratings were more likely to issue fixed-rate debt and swap into floating-rate debt. In short, the results supported the conclusion that the yield spread has a positive and significant effect on swap usage. In addition, Batram et al. (2006) also discovered that only the firm that using interest rate derivatives had a positive valuation effect. Moreover, Covitz and Sharpe (2005) investigated that smaller firms have more exposure on interest rate from their liabilities compared to the larger firms. Therefore, smaller firms tend to use derivative to neutralize their interest rate exposures whereas, larger firms will use their choice of debt structure to limit the interest rate exposures rather than with derivatives.
However, the authors examined non-financial firms with their use of commodity derivatives, currency and interest rate, and their finding showed a negative impact of interest rate derivatives on firm value (Nelson et al., 2005). Besides, Nguyen and Fatt (2007) also found that there was an adverse relationship between firm value and derivatives use. They investigated both the relationship between firm value and aggregate measure of derivatives as well as the impact that individual types of derivatives potentially have on firm market value. Their result strongly indicated that the use of interest rate derivatives in particular and the use of derivatives in general lead to a reduction in firm value or a „derivative user? discount.
As a result, different authors came out with different result regarding to the issue of whether the interest rate derivative can affect firm value. Some
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The Impact of Derivatives on Firm Value
authors found that there was a positive effect of interest rate derivatives on firm value and vice versa. Therefore, the hypothesis was proposed as:
H1: Interest rate derivative is positively related to firm value
3.6.2 Foreign Currency Derivatives
Firms in the plantation, industrial product, trading services, and consumer products manufacturing sectors are the main users of the FCDs in Malaysia. From the research of Hentschel and Kothari (2000), they found there was no significant relationship between the volatility of a firm?s stock price and the size of the firm?s derivative position. Besides that, Mag ee (2009) suggested the foreign currency hedging has no impact on firm value after controlling for the dependence of foreign currency hedging on past amounts of firm.
Bartram et al. (2006) studied on the purpose of using derivatives by a firm. The firms with foreign currency transactions tend to use foreign currency derivatives, this is because foreign currency transaction normally comes with foreign currency risk. Once the risk has been hedged, shareholder wealth maximization will be achieved, therefore firm value will increase. From the findings of Allayannis and Weston (1998), there was evidence that the use of currency derivative was in a positive association with the firm value. Besides that, Makar and Huffman (2008) found US foreigndenominated debt issuers could hedge short-term risk effectively by using foreign currency derivatives. Thus, we develop our research hypothesis as:
H1: Currency derivative is positively related to firm value
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The Impact of Derivatives on Firm Value
3.6.3 Commodity Derivatives
From the research of Chang et al. (2005), they found that hedging activities in an operation has a significant impact on firm value. They conducted a study on the impact of hedging activities of Canadian oil and gas companies on their stock return and firm value for the period of 20002002. The impact of hedging on firm value was measured by Tobin's Q ratio by using both linear and nonlinear models. The result indicated that in particular hedging for gas, together with profitability, leverage and reserves has a significant impact on firm value.
Besides that, Bartram et al. (2006) also agreed that the use of commodity derivative will improve the firm value. They conducted a survey on the effect of derivative use on firms? risk measures and value by using a large sample of 6,888 non-financial firms from 47 countries. They found strong evidence that the use of financial derivatives reduced both total risk and systematic risk and there was a positive relationship of derivative used on firm value but not strong.
Another research from Carter et al. (2002) investigated jet fuel hedging behavior of firms in US airline industry during 1994-2000 to examine whether such hedging was a source of value for these companies. The result showed that they found evidence to support the view that airlines, on average, increased firm value by using derivatives to hedge against changes in jet fuel prices.
However, Jin and Jorion (2006) found that there was no difference in firm values between firms that hedge and firms that do not hedge. They used the sample of 119 U.S. oil and gas produce from 1998 to 2001 with the measurement of Q ratios.
Nelson et al. (2005) examined the annual stock performance of 1,308 U.S. firms over the period per year 1995-1999. They found that firms that hedge
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The Impact of Derivatives on Firm Value
outperformed other securities by 4.3 percent per year on average. However, they found no abnormal returns for firms hedging either interest rates or commodities. From all the researchers? works stated as above, they have found a different answer about the issue of whether the firm value will be improved if the firm undergoing hedging activities. In common sense, if a firm was using derivative to hedge the firm?s risk in a correct manner, theoretically it will reduce the firm?s risk overall, then it should lead to firm value improvement. Thus, we developed the hypothesis as:
H1: The commodity derivative is positively related to firm value
3-14
The Impact of Derivatives on Firm Value
CHAPTER 4 DATA ANALYSIS
4.1
Descriptive Statistic
Table 4.1 to 4.4 provide a summary of the descriptive statistic of dependent variable (Tobin?s Q) and i ndependent variables (interest rate derivative, commodity derivative, currency derivative, ROA, ROE, firm size, leverage, investment growth and dividend per share) from year 2007 to 2009 and panel data which includes all the three years. The mean, median, maximum, and minimum of each variable are shown in the tables.
From the result of descriptive statistic of pooled data shown in Table 4.1, it showed that the mean (medium) of Tobin?s Q was 0.8634 (0.5576). This indicated that the firm market value was less than the recorded value of the assets of the company, in other words Malaysia listed companies have been undervalued by the market. The profitability ratios (ROE and ROA) recorded a mean (medium) value of 0.1226 (0.11135) and 0.0794 (0.0664) respectively. While for the leverage, it has recorded the mean of 0.4046 which indicated that Malaysia listed companies in average financed their assets by debt in around 40.46 percent. In terms of dividend per share, it showed that Malaysia listed companies in average has paid out the dividend of RM 0.10 per shares to their shareholders. Lastly, the investment growth (ratio of CAPEX to market value of firm) has recorded the mean of 38.21 percent.
For the descriptive statistic of year 2007 shown in Table 4.2, it showed that the mean (medium) of Tobin?s Q is 1.1462 (0.726980). This indicated that their market value was more than the recorded value of the assets of the company, in other words, Malaysia listed companies in average has been overvalued by the market in 2007. The profitability ratios (ROE and ROA)
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The Impact of Derivatives on Firm Value
recorded the mean (medium) value of 15.16 percent (13.18 percent) and 9.57 percent (7.28 percent) respectively. While the mean value of leverage was 0.2676777 which indicated that Malaysia listed companies on average financed their assets by debt in around 26.77 percent. In terms of the investment growth, it has recorded the mean of 26.04 percent. Lastly, Malaysia listed companies in average paid RM 0.10 dividends per share to their shareholders in 2007.
Followed by the descriptive statistic of 2008 shown in Table 4.3, it showed that the mean (median) of Tobin?s Q ratio was 0.7369. This indicated that their market value was less than the recorded value of the assets of the company, in other words, Malaysia listed companies have been undervalued by the market. While the mean of profitability ratios (ROE and ROA) were 11.30 percent (11.68 percent) and 7.59 percent (6.80 percent) respectively. Whereas the mean of leverage was 0.56675 which indicated that 56.69 percent of the assets of Malaysia listed companies were financed by debt. In terms of the investment growth, the mean value was recorded at 0.523241 or 52.32 percent. Lastly, Malaysia listed companies in average have paid out dividend of RM 0.09 per share to their shareholders in 2008.
Lastly in Table 4.4, it shows the descriptive statistic for the year 2009. The mean of Tobin?s Q for Malaysia listed companies was 0.7991, this indicated that the Malaysia listed companies in average has been undervalued by the market in 2009. The profitability ratios (ROE and ROA) have recorded a mean (median) value of 10.32 percent (9.64 percent) and 6.66 percent (5.69 percent) respectively. Whereas the mean value of leverage was 0.379421 which indicated that 37.94 percent of the assets of Malaysia listed companies were financed by debt. In terms of the investment growth, the mean value was recorded at 36.28 percent. Besides that, Malaysia listed companies in average has paid out the dividend of RM 0.11 per share to their shareholders in 2009.
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The Impact of Derivatives on Firm Value
Table 4.1: Descriptive Statistic for Pooled Data
Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations
TOBIN?S Q 0.863412 0.557654 8.836000 -0.403709 1.070044 3.243932 17.71621 9699.715 0.000000 777.0706 1029.350 900
SIZE 9.026994 8.969425 10.85350 5.842217 0.572208 -0.036297 6.593048 484.3223 0.000000 8124.295 294.3524 900
ROE 0.122577 0.111350 2.326960 -1.890900 0.220637 1.003207 47.88707 75707.81 0.000000 110.3197 43.76378 900
ROA LEVERAGE 0.079398 0.404621 0.066443 0.124200 2.701200 34.36550 -0.412100 -0.684500 0.127190 1.327634 10.09638 19.28258 205.1491 479.5712 1547700. 0.000000 71.45822 14.54348 900 8572776. 0.000000 364.1589 1584.588 900
INVESTMET GROWTH 0.382106 0.101006 8.787456 0.000100 0.767974 4.353325 30.50664 31215.79 0.000000 343.8953 530.2163 900
DPS 0.101050 0.040000 2.450000 0.000000 0.211906 5.873345 49.73962 87096.64 0.000000 90.94500 40.36875 900
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The Impact of Derivatives on Firm Value
Table 4.2: Descriptive Statistic for 2007
Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations
TOBIN?S Q 1.146171 0.726980 20.13330 -0.290100 1.687333 6.078472 58.94660 40972.66 0.000000 343.8514 851.2811 300
SIZE 8.968566 8.926669 10.83070 5.842217 0.621360 -0.556215 7.656380 286.4922 0.000000 2690.570 115.4404 300
ROE 0.151579 0.131750 2.326960 -0.673300 0.224883 5.274280 51.26643 30511.50 0.000000 45.47378 15.12115 300
ROA LEVERAGE 0.095665 0.267677 0.072769 0.096440 2.701200 3.044900 -0.405100 -0.684500 0.176707 0.457681 10.87435 3.128022 159.5770 15.28245 312366.9 0.000000 28.69947 9.336368 300 2374.958 0.000000 80.30315 62.63222 300
INVESTMENT GROWTH 0.260382 0.077100 2.273400 0.000100 0.447515 2.684497 10.15063 999.4693 0.000000 78.11474 59.88058 300
DPS 0.101677 0.040000 2.450000 0.000000 0.221612 6.473189 58.02580 39943.09 0.000000 30.50310 14.68445 300
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The Impact of Derivatives on Firm Value
Table 4.3: Descriptive Statistic for 2008
Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations
TOBIN?S Q 0.736890 0.430700 9.396400 -0.403709 1.098916 4.328630 28.90108 9322.676 0.000000 221.0671 361.0775 300
SIZE 9.037429 8.962243 10.84410 5.843506 0.557227 0.081503 6.574752 160.0678 0.000000 2711.229 92.84013 300
ROE 0.112971 0.116800 1.995400 -1.890900 0.234531 -1.428010 41.79082 18911.05 0.000000 33.89115 16.44644 300
ROA LEVERAGE 0.075936 0.566765 0.068019 0.168000 0.726900 34.36550 -0.412100 0.000000 0.096291 2.149144 0.521425 13.34520 14.91633 206.2192 1788.581 0.000000 22.78073 2.772314 300 525130.2 0.000000 170.0295 1381.027 300
INVESTMENT GROWTH 0.523241 0.129129 8.787456 0.000200 1.051162 3.805062 21.51589 5009.400 0.000000 156.9723 330.3772 300
DPS 0.092842 0.040000 1.450000 0.000000 0.173482 4.356782 27.33534 8351.690 0.000000 27.85270 8.998677 300
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The Impact of Derivatives on Firm Value
Table 4.4: Descriptive Statistic for 2009
Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis Jarque-Bera Probability Sum Sum Sq. Dev. Observations
TOBIN?S Q 0.799126 0.493094 8.750100 -0.212900 0.982379 3.615790 22.31386 5316.511 0.000000 239.7377 288.5555 300
SIZE 9.074988 8.984830 10.85350 7.835988 0.531055 0.776749 3.626742 35.07698 0.000000 2722.496 84.32395 300
ROE 0.103184 0.096361 1.700000 -1.858000 0.198686 -1.232071 48.51502 25971.12 0.000000 30.95513 11.80331 300
ROA 0.066594 0.056944 0.697100 -0.410700 0.087756 1.374339 16.84041 2488.903 0.000000 19.97807 2.302620 300
LEVERAGE 0.379421 0.122650 5.120300 0.000000 0.652305 3.306734 17.35362 3122.054 0.000000 113.8263 127.2249 300
INVESTMENT GROWTH 0.362754 0.099450 4.805500 0.000879 0.657876 3.174749 15.14826 2348.705 0.000000 108.8263 129.4076 300
DPS 0.108714 0.040000 2.360000 0.000000 0.235930 5.664781 43.81736 22430.20 0.000000 32.61420 16.64324 300
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The Impact of Derivatives on Firm Value
4.2
Pearson Correlation
Table 4.5 reports the Pearson correlation coefficients between the dependent variable (Tobin?s Q) and explanatory variables. It reported a set of bivariate correlation coefficients results between Tobin?s Q and all independent variables. Tobin?s q, proxy of the firm value, was neg atively and significantly correlated with interest rate derivative used at 5 percent level but was positively correlated with commodity and currency derivatives used. The correlation between interest rate derivative and Tobin?s Q was only -0.07. On the other hand, the correlation between Tobin?s Q and commodity derivative was 0.011; whereas the correlation between Tobin?s Q and currency derivatives was 0.03. ROA, ROE and DPS were found positively and significantly correlated with firm value at 1 percent level. The correlation between firm value and ROA was high at 0.517. While the correlation between firm value and ROE was also high at 0.475. The correlation between DPS and firm value was 0.456. Besides, firm size was also found to be negatively correlated with firm value where the correlation between the two variables was -0.059. On the other hand, firm value was negatively and significantly correlated with leverage and investment growth at 1 percent level. The correlation between firm value and leverage was 0.101. While the correlation between Tobin?s Q and investment growth was -0.117.
4.3
Ordinary Least Square Result
At first, we conducted a simple ordinary least square (OLS) as shown in Table 4.6. It presented the detail of OLS results with and without the adjustment of heteroskedasticity in 2007, 2008, 2009 and pooled data. The results were separated into two columns for each years and pooled
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The Impact of Derivatives on Firm Value
data. One is the normal OLS results before the adjustment of heteroskedasticity (OLS) while the other one is the OLS results with the adjustment of heteroskedasticity (With H-C).
The firm size was significantly (0.05) and negatively related with firm value in 2007 without the adjustment of heteroskedasticity but insignificant with the adjustment of heteroskedasticity. This indicated that the firm value would decrease as its firm size to increase. However in 2008, both OLS with and without the adjustment of heteroskedasticity were significant positively related to firm value at one percent and five percent level of significance. Whereas the result in 2009 showed that it was not significant at all. In the pooled data, negative relationship was significantly (0.01) shown on both with and without the adjustment of heteroskedasticity.
In terms of return on equity (ROE), it was not significant in all the three years and pooled data with and without the adjustment of
heteroskedasticity. In terms of the return on assets (ROA), the result showed that it was significantly and positively related to firm value in all the three years and also pooled data.
Besides that, both of the leverage and Investment growth were not significant in all the three years and pooled data without the adjustment of heteroskedasticity. As for dividend per share, it was significantly and positively related to firm value with and without the adjustment of heteroskedasticity in all the years (except 2008) and pooled data. It was consistent with the findings of Lang and Litzenberger (1989), Azhagaiah and Priya (2008), and Lintner (1956). They suggested that dividend announcement would affect the stock price of a firm, because market believed that valuable information about the firm future prospect and growth could be conveyed by an announcement of dividend.
In terms of the three types of derivatives, the commodity derivative was not significant in all the 3 years and also pooled data. While for the foreign
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The Impact of Derivatives on Firm Value
currency derivative, it was only significant in 2007 and this was consistent with the finding of Allayannis and Weston (2001), and Bartram et al (2006) which stated that FCD has significant impact (positive effect) on firm market value.
Whereas for the interest rate derivative, it was only the one of the derivatives which has the negative impact on firm value in 2007, 2008 and pooled data with the adjustment of heteroskedasticity. Our result supported the finding of Khediri (2010) in which there was a negative relationship between interest rate derivatives and firm value. However, this was not consistent with the findings of Singh (2009), and Batram et al (2006) which pointed out that firm that using interest rate derivatives have a positive valuation effect.
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The Impact of Derivatives on Firm Value
Table 4.5: Pooled Correlation Matrix Interest rate Commodity Currency Tobin?s Q Derivatives Derivatives Derivatives -0.070* 1 0.011 0.030 0.037 0.740 0.361 ** 0.115 0.176** 1 0.001 0.000 0.132** 1 0.000 1 Size -0.059 .0075 0.188** 0.000 0.044 0.184 0.070* 0.035 1 Leverage -0.101** 0.003 0.082* 0.014 -0.004 0.916 0.009 0.794 0.176** 0.000 1 ROA 0.517** 0.000 0.000 0.999 0.029 0.377 0.033 0.329 -0.067* 0.046 -0.135** 0.000 1 ROE 0.475** 0.000 0.038 0.251 0.051 0.125 0.077* 0.021 -0.002 0.948 -0.114** 0.001 0.802** 0.000 1 Investment Growth -0.117** 0.000 0.001 0.984 -0.031 0.351 -0.069* 0.037 0.055 0.101 0.406** 0.000 -0.139** 0.000 -0.111** 0.001 1 DPS 0.456** .000 -0.011 0.750 0.044 0.188 0.158** 0.000 0.095** 0.004 -0.084* 0.011 0.341** 0.000 0.413** 0.000 -0.110** 0.001 1
Tobin?s Q Interest rate Derivatives Commodity Derivatives Currency Derivatives Size Leverage ROA ROE Investment Growth DPS
*p<0.05, **p<0.01
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The Impact of Derivatives on Firm Value
Table 4.6: Regression Results of the Factors That Affect Firm Value Variable 2007 2008 2009 OLS With H-C OLS With H-C OLS With H-C Constant 4.1055 4.1055 -1.5763 -1.5763 0.7463 0.7463 -0.3730** 0.2129** 0.2129*** Size -0.3730 -0.0543 -0.0543 (0.1578) (0.2512) (0.1060) (0.0775) (0.0863) (0.0863) ROE 0.6464 0.6464 -0.4545 -0.4545 -0.2871 -0.2871 (0.9107) (1.0690) (0.4918) (0.9300) (0.3266) (0.4462) 1.3670* 5.8683*** 5.8682*** 6.2989*** 6.2989*** ROA 1.3670 (1.0740) (0.7236) (1.2728) (1.6088) (0.7827) (1.6668) Leverage -0.0708 -0.0708 -0.0022 -0.0022 0.0724 0.0724 (0.2199) (0.1207) (0.0304) (0.0211) (0.0723) (0.0601) Investment Growth -0.1661 -0.1661* 0.0663 0.0663 0.0469 0.0469 (0.2041) (0.0971) (0.0623) (0.0413) (0.0645) (0.0582) 1.7382*** 1.7382*** DPS 0.5729 0.5729 1.2593*** 1.2593*** (0.5055) (0.4439) (0.3685) (0.4377) (0.2094) (0.3318) Commodity Derivative -0.2274 -0.2274 0.0979 0.0979 0.0502 0.0502 (0.3908) (0.2353) (0.0989) (0.1163) (0.1694) (0.1144) 0.4722** Currency Derivative 0.4722 -0.0687 -0.0687 -0.0596 -0.0596 (0.2096) (0.3305) (0.1246) (0.1297) (0.0935) (0.0793) -0.402*** -0.402*** Interest rate Derivative -0.3845 -0.3845** -0.0563 -0.0563 (0.2396) (0.1556) (0.1458) (0.1075) (0.1105) (0.0923) R² 0.1905 0.1905 0.2425 0.2425 0.4993 0.4993 7.5826*** 7.5826*** 10.3172*** 10.3172**** 32.1267*** 32.1267*** F-test *sig at 0.1, **sig at 0.05, ***sig at 0.01, std error are given in parentheses Dependent variable: Firm Value (T obin?s Q) Pooled OLS With H-C 1.3817 1.3817 -0.099* -0.0990* (0.0522) (0.0530) 0.3083 0.3083 (0.2251) (0.5300) 2.9688*** 2.9688*** (0.3806) (1.0564) 0.0051 0.0051 (0.0240) (0.0146) -0.0393 -0.0393 (0.0411) (0.0287) 1.5908*** 1.5908*** (0.1512) (0.2516) -0.0155 -0.0155 (0.0753) (0.0366) -0.055 -0.055 (0.0645) (0.0609) -0.1487* -0.1487** (0.0760) (0.0712) 0.3650 0.3650 56.8381*** 56.8381***
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The Impact of Derivatives on Firm Value
4.4
Pooled Data Analysis
In this study, panel data technique was used. Table 4.7 shows the regression results of the model that examines the effect of the use of derivative on firm value. The model was derived based on pooled effect (PE), fixed effect (FE), and random effect (RE) methods. The original results of all the three methods that generated from E-view are shown in Appendix 1 (PE), Appendix 2 (FE), and Appendix 3 (RE). In order to choose which model is more suitable for estimating T obin?s Q equation, the Hausman specification test (Hausman, 1978)15 as shown in Table 4.8 was conducted to statistically test these three methods. If the model is correctly specified and individual effect are uncorrelated with the dependent variable, the fixed effect and random effect estimators should not be statistically different. The statistic reported in Table 4.8 showed that the null hypothesis, the individual effects were uncorrelated with the other regressors and was rejected in one percent significance level. The result suggested that the fixed effect model was most appropriate in estimating the Tobin?s Q equation.
From the results derived from fixed effect model, firm size was found to be significantly and negatively related to the firm value. This represented the larger the firm size, the lower the firm value. Our result supported the findings of Mak and Kusnadi (2005) in which there was an inverse relationship between firm value and firm size. However, it was not consistent with the findings of Ushijima (2003) in which the value of firm increased with its firm size.
Besides, we have observed a significant positive relationship between the leverage and firm value. It was consistent with the findings of Ward and Price (2006). They indicated that an increase in debt-equity ratio, shareholder returns would also to increase. However, Salehi and Biglar
15
Hausman, J. (1978). Specification tests in econometrics, Econometrica, 46, 1251-1271. 4-12
The Impact of Derivatives on Firm Value
(2009), and Rayan (2008) concluded that firm value and firm leverage were negatively correlated.
Furthermore, there was a significant positive relationship between firm value and ROA at one percent level of significance. Modigliani and Miller (1958) stated that a firm?s value could be maximized by using more debt in its capital structure; debt allowed firm to decrease their average cost of capital and enhance profitability as long as its ROA was greater than the before-tax interest paid on debt. ROE was found to be insignificant in determining the firm value.
In addition, we found that there was a negative relationship between firm value and investment growth at one percent level of significance. According to research done by Chung et al. (1998), market perceived that firms with low Tobin?s Q ratios having a lack of valuable or low profitable investment opportunities, therefore market reactions generally less positive about the announcements of capital expenditures increase by such firm; but tend to view favorably if it reduced capital expenditures. During the period of 2007-2009, Malaysia?s economy has been badly affected by the US subprime crisis, therefore the market may perceived the company within the country has lack of valuable investment opportunity and did not feel optimistic if firms increased their capital spending.
The results indicated that the dividend was positively related to firm value and statistically significant at five percent level. It was consistent with the findings of Lang and Litzenberger (1989), Azhagaiah and Priya (2008), and Lintner (1956). They suggested that an announcement of dividend will increase the stock price and vice versa. The reason was, managers were believed to hold reliable insider information about the future financial position of a company and they could convey this information to investor through dividend distributions. Thus, an announcement of a dividend was believed to convey certain valuable information about the firm future prospect and growth to the public.
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The Impact of Derivatives on Firm Value
In terms of the three types of derivatives, the results showed that interest rate derivative has no significant impact on firm value. It was consistent with the findings of Nelson et al. (2005). However, Singh found that lodging firms were positively exposed to interest rate risk. Therefore a further empirical research should be conducted on this argument.
Besides that, the commodity derivative was also insignificant related to the firm value. This result was consistent with the research of Jin and Jorion (2004), they found that hedging did not affect firm value and there were no differences in firm?s value between firm that hedge and firm that d id not hedge. Besides that, Nelson et al. (2005) also found out there was no abnormal return for firms hedging either by interest rate or commodity derivatives.
From the regression result, only the currency derivative was significantly related to the firm value; however, it was in negative relationship. This indicated that if the firms used FCD, they might experience loses. This was inconsistent with the finding of Allayannis and Weston (2001) and Bartram et al. (2006). The later researchers pointed out FCD has a significant positive effect on firm market value. However, our result supported the finding of Khediri (2010) in which derivative has a negative relationship with the firm value.
Furthermore, Nguyen and Faff (2003) discovered that the impact of FCD usage on exchange risk exposure was generally weak and lacks consistency. Bartram et al. (2004) revealed evidence of positive value effect of general derivatives use but only limited for firms without exposure. The impact of FCD usage, in particular, was found to be insignificant. Bodnar, Haty and Marston (1996)16 provided extensive survey evidence on corporate derivatives use. Their evidence suggested that firms typically hedged with derivatives but did so imperfectly.
16
Bodnar, G.M., Haty, G.S., & Marston, R.C. (1996). 1995 Wharton survey of derivatives usage by U.S. non-financial firms. Financial Management, 25(4), 113-133. 4-14
The Impact of Derivatives on Firm Value
Table 4.7: Pooled Data Analysis of Value Effects of Derivatives Use Decision Variables Constant Size Random 2.1403 -0.1626*** (0.058) ROE -0.0172 (0.1753) 2.1103*** ROA (0.2889) Leverage 0.0231 (0.0192) -0.1639*** Investment Growth (0.0404) 1.1048*** DPS (0.1411) Commodity Derivative -0.0005 (0.0594) Currency Derivative -0.0846 (0.0766) Interest rate Derivative -0.0384 (0.0958) R² 0.2091 Hausman Test 0.0000 56.8381*** 11.5807*** 26.1374*** F-test *sig at 0.10, **sig at 0.05, ***sig at 0.01, std error are given in parentheses Dependent Variable: Firm Value (Tobin?s Q) Pooled 1.3817 -0.0990* (0.0522) 0.3083 (0.2251) 2.9688*** (0.3806) 0.0051 (0.0240) -0.0393 (0.0411) 1.5908*** (0.1512) -0.0155 (0.0753) -0.055 (0.0645) -0.1487* (0.0760) 0.365 Fixed 3.0906 -0.2528*** (0.0854) -0.3049 (0.1927) 1.7880*** (0.3117) 0.0432** (0.0219) -0.2507*** (0.0509) 0.3811** (0.1782) 0.0045 (0.0650) -0.2134* (0.1261) 0.2885 (0.1867) 0.8579
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The Impact of Derivatives on Firm Value
Table 4.8: Hausman Specification Test Correlated Random Effects - Hausman Test Pool: HM Test cross-section random effects Test Summary Cross-section random Chi-Sq. Statistic Chi-Sq. d.f. 111.869283 9 Prob. 0.0000
Cross-section random effects test comparisons: Variable INTDERIVATIVES? COMDERIVATIVES? CURDERIVATIVES? SIZE? LEVERAGE? ROA? ROE? INVESGROWTH? DPS? Fixed 0.288476 0.004511 -0.213413 -0.252805 0.043157 1.788026 -0.304914 -0.250748 0.381134 Random -0.038449 -0.000506 -0.084614 -0.162597 0.023077 2.110258 -0.017187 -0.163891 1.104780 Var(Diff.) 0.025644 0.000699 0.010048 0.003943 0.000108 0.013711 0.006400 0.000954 0.011865 Prob. 0.0412 0.8495 0.1988 0.1508 0.0534 0.0059 0.0003 0.0049 0.0000
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CHAPTER 5 CONCLUSION
5.1
Conclusion
The study examined the impact of derivatives on the sample of 300 Malaysia non-financial firms over the period 2007-2009. From the regression results, we concluded that interest rate derivatives and commodity derivatives have no significant impact on firm value, this result supported the finding of Nelson et al. (2005) in which the usage of these two derivatives have no effect on the firm?s market value. On the other hand, the currency derivatives were partially significant but it is negatively related to the firms? market value. In other words, if the firm performs hedging activities by using currency derivatives, it will lower down its market value. This result was inconsistent with the findings of Allayannis and Weston (2001), Pramborg (2003), Nelson et al. (2005), and Allayannis et al. (2009). However, from the research of Nguyen and Faff (2003) they found currency derivatives usage was generally weak and lack consistent.
In terms of other explanatory variables, firm size and investment growth have a strong significant impact on firm value but in negative relationship. For leverage, ROA, and dividend per share, there were significant positively related to the firms? market value.
Therefore, we made a conclusion for the hypotheses that we developed in chapter 3: 1. Interest rate derivatives: Do not reject H0. There is no evidence shows that interest rate derivative is positively related to firm value. 2. Currency derivatives: Do not reject H0. There is no evidence shows that currency derivative is positively related to firm value.
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The Impact of Derivatives on Firm Value
3. Commodity derivatives: Do not reject H0. There is no evidence shows that commodity derivative is positively related to firm value.
From the results, it seems like the hedging activities is independent from the management especially both of the commodity and interest rate derivatives. While for the currency derivatives is valued at a discount. The question of why currency derivatives use is valued at discount in Malaysia deserves further research.
5.2
Implications
Our results showed that the use of financial derivatives towards the potential impact on firms value in a broad sample of non-financial firms from 2007 to 2009. The result from the finding may be implying that how the firms truly use of financial derivatives and shareholder value influence by the finance policy.
From the regression results, the interest rate derivatives and commodity derivatives were not significantly and positively related to firm value, this implied that the use of interest rate derivatives and commodity derivatives did not have any impact on firms market value, hence whether or not the company has used these two derivatives would not improve company value and maximize shareholder wealth. Shareholder may find that interest rate derivatives and commodity derivatives are useless for firms and request management team to cut off the expenditure spend on derivatives and transfer the capital to other more profitable investments. Even result showed insignificant, it is still consistent with the findings of Nelson et al. (2005) and Khediri (2010) but it is inconsistent with other finding such as Ameer (2009), Covitz and Sharpe (2005), Bartram et al. (2006), Carter et al. (2002).
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The Impact of Derivatives on Firm Value
The currency derivative was partially significant but it was negatively related to the firms? market value. In other words, the currency derivatives has a negative impact on Malaysia?s firm value, which means if the firm performs hedging activities by using currency derivatives, it will lower down its market value. This implies that management of the company may avoid using currency derivatives. Unlike interest rate and commodity derivatives, shareholder may avoid to invest in firms that use currency derivative as policy in managing currency risk. Firms with currency risk may have to choose other instruments to hedge the risk or alternative method to minimize it. Our result did not consistent with the findings of Allyannis and Weston (2001), Pramborg (2003), Nelson et al. (2005), and Allyannis et al. (2009). However, from the research of Nguyen and Faff (2003) they found currency derivatives usage was generally weak and lack consistent.
5.3
Limitations and Recommendations
We find some limitations on this study. Firstly, our data collection process was only restricted on companies? financial reports. All of the data that we needed in the research was based on the financial information of the Malaysia top 300 non-financial firms. Therefore, we collected the data such as derivative usage, ROA, total assets, market capitalization, net profits, current liabilities and others by looking at the companies? financial report one by one. This was time consuming because we need to collect the financial data of 300 companies for 3 years. Besides that, the financial report is less accuracy in communicating the real value of the enterprise and its future performance potential. Therefore, in order to improve the accuracy of the data that we collected, our suggestion is to use the online databases which are chargeable, such as OSIRIS and Bursa Station. These two online databases provide the financial statements for all the Malaysia companies in detailed. It will also show the financial reports of a particular company for few years in a page, it is easier for the analyst to collect data and compare the performance of a company across the time
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The Impact of Derivatives on Firm Value
series. However, these two online databases are chargeable, we have to pay before we can access to it.
Secondly, differences in accounting methods between companies will make it difficult in comparing the performance of the companies. For example, some firms may use LIFO method to prepare their financial report while some may use average cost method. Then direct comparison of financial data such as cost of goods sold between two companies may be misleading. The misleading value of cost of goods sold will have an impact on the gross profit and hence the net profit. Thus, it will lower down the accuracy of analysis by comparing the companies with different accounting method.
Besides that, some of the journals are chargeable. In Chapter 2, we conducted a literature review by reading on the journals that done by other researchers on the topic which was similar to our research. For some of the important journal which is directly discussing their findings on the impact on derivatives on firm value, we only found its paragraph of abstract but not in full journals, we are required to pay for it prior to access to the whole journals. Students may not afford to pay for it. Our suggestion is that the faculty should provide more and more free trial accessing to the external database which could let the students easily find the journals in completing their thesis.
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APPENDICES
Appendix 1: Result of Pooled Effect
Dependent Variable: TOBINSQ? Method: Pooled Least Squares Date: 03/01/11 Time: 18:38 Sample: 2007 2009 Included observations: 3 Cross-sections included: 300 Total pool (balanced) observations: 900 Variable C INTDERIVATIVES? COMDERIVATIVES? CURDERIVATIVES? SIZE? LEVERAGE? ROA? ROE? INVESGROWTH? DPS? R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) Coefficient 1.381719 -0.148699 -0.015490 -0.054995 -0.099007 0.005128 2.968806 0.308347 -0.039265 1.590784 0.364986 0.358564 0.856995 653.6521 -1133.126 56.83813 0.000000 Std. Error 0.468759 0.076007 0.075347 0.064544 0.052188 0.024043 0.380586 0.225074 0.041087 0.151171 t-Statistic 2.947609 -1.956399 -0.205578 -0.852067 -1.897131 0.213266 7.800624 1.369983 -0.955676 10.52305 Prob. 0.0033 0.0507 0.8372 0.3944 0.0581 0.8312 0.0000 0.1710 0.3395 0.0000 0.863412 1.070044 2.540280 2.593640 2.560664 0.820250
Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat
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The Impact of Derivatives on Firm Value
Appendix 2: Result of Fixed Effect
Dependent Variable: TOBINSQ? Method: Pooled Least Squares Date: 03/01/11 Time: 18:45 Sample: 2007 2009 Included observations: 3 Cross-sections included: 300 Total pool (balanced) observations: 900 Variable C INTDERIVATIVES? COMDERIVATIVES? CURDERIVATIVES? SIZE? LEVERAGE? ROA? ROE? INVESGROWTH? DPS? Fixed Effects (Cross) 1--C 2--C 3--C 4--C 5--C 6--C 7--C 8--C 9--C 10--C 11--C 12--C 13--C 14--C 15--C 16--C 17--C 18--C 19--C 20--C 21--C 22--C 23--C 24--C 25--C 26--C 27--C 28--C 29--C 30--C Coefficient 3.090641 0.288476 0.004511 -0.213413 -0.252805 0.043157 1.788026 -0.304914 -0.250748 0.381134 0.301243 0.323240 0.414843 -0.226266 0.900720 0.407761 2.794695 0.876661 0.640940 0.891262 -0.128941 -0.010897 6.764876 0.126781 0.096075 2.867060 0.105850 4.707487 -0.516373 -0.235599 -0.350889 -0.168716 0.387331 0.580395 0.027387 -0.097769 1.768882 0.351990 0.110320 1.452386 Std. Error 0.769901 0.186593 0.065038 0.126143 0.085447 0.021865 0.311705 0.192656 0.050890 0.178242 t-Statistic 4.014335 1.546018 0.069360 -1.691834 -2.958603 1.973835 5.736271 -1.582683 -4.927235 2.138289 Prob. 0.0001 0.1226 0.9447 0.0912 0.0032 0.0489 0.0000 0.1140 0.0000 0.0329
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The Impact of Derivatives on Firm Value
31--C 32--C 33--C 34--C 35--C 36--C 37--C 38--C 39--C 40--C 41--C 42--C 43--C 44--C 45--C 46--C 47--C 48--C 49--C 50--C 51--C 52--C 53--C 54--C 55--C 56--C 57--C 58--C 59--C 60--C 61--C 62--C 63--C 64--C 65--C 66--C 67--C 68--C 69--C 70--C 71--C 72--C 73--C 74--C 75--C 76--C 77--C 78--C 79--C 80--C 81--C 82--C 83--C
0.865832 0.066042 -0.300108 0.826531 -0.377849 0.298821 -0.254500 -0.105425 1.936487 0.090427 1.123728 -0.615710 -0.328558 -0.517337 0.420870 -0.144103 -1.039050 1.340976 -0.137368 -0.281652 -0.332505 -0.277337 0.064760 0.684611 -0.228950 0.257205 0.401800 1.791787 -0.149544 2.164580 -0.440664 0.092259 0.748344 0.739806 0.006138 1.244382 0.858343 0.386741 1.418879 0.423631 0.711054 0.211605 1.832551 1.427216 0.509018 0.649600 0.488031 0.464006 0.289630 2.891073 0.854196 0.932140 0.437455
A-3
The Impact of Derivatives on Firm Value
84--C 85--C 86--C 87--C 88--C 89--C 90--C 91--C 92--C 93--C 94--C 95--C 96--C 97--C 98--C 99--C 100--C 101--C 102--C 103--C 104--C 105--C 106--C 107--C 108--C 109--C 110--C 111--C 112--C 113--C 114--C 115--C 116--C 117--C 118--C 119--C 120--C 121--C 122--C 123--C 124--C 125--C 126--C 127--C 128--C 129--C 130--C 131--C 132--C 133--C 134--C 135--C 136--C
0.112123 -0.188489 -0.100831 -0.148119 3.543283 0.732303 0.328476 0.548549 -0.211429 0.312736 0.119293 0.744009 0.497300 0.686946 0.738498 0.212651 0.854341 0.880783 -0.023158 0.293555 0.342462 1.137522 1.157321 0.428442 0.069574 0.476993 0.051904 0.210015 2.226218 0.716392 0.736729 0.615652 0.426039 1.356178 -0.595799 0.081541 1.188969 -0.476879 -0.503446 -0.125268 -0.469239 -0.289715 -0.517805 -0.173951 -0.735252 -0.095181 -0.283080 -0.843831 -0.422299 -0.403663 -0.805084 -0.907993 -0.177528
A-4
The Impact of Derivatives on Firm Value
137--C 138--C 139--C 140--C 141--C 142--C 143--C 144--C 145--C 146--C 147--C 148--C 149--C 150--C 151--C 152--C 153--C 154--C 155--C 156--C 157--C 158--C 159--C 160--C 161--C 162--C 163--C 164--C 165--C 166--C 167--C 168--C 169--C 170--C 171--C 172--C 173--C 174--C 175--C 176--C 177--C 178--C 179--C 180--C 181--C 182--C 183--C 184--C 185--C 186--C 187--C 188--C 189--C
-0.839133 -0.567085 -0.371744 0.370768 -0.744399 -0.291946 -0.513954 0.435673 -0.319179 -0.530779 0.873075 0.564812 0.176746 -1.204041 -0.383972 -0.682271 -0.560246 0.063033 -0.044211 -0.903405 -0.201357 0.453771 -0.123317 1.678678 -0.619737 -0.617862 -0.770390 -0.887731 -1.175807 -1.293682 -0.795160 0.145443 -0.417252 -0.080232 -0.882661 -0.704096 -0.024329 -1.012929 -0.590030 0.137834 -0.729940 0.045828 -0.170101 -0.738802 0.253380 0.768510 -0.168500 -0.658571 -0.643194 -0.310412 -0.389592 -0.536898 -0.179795
A-5
The Impact of Derivatives on Firm Value
190--C 191--C 192--C 193--C 194--C 195--C 196--C 197--C 198--C 199--C 200--C 201--C 202--C 203--C 204--C 205--C 206--C 207--C 208--C 209--C 210--C 211--C 212--C 213--C 214--C 215--C 216--C 217--C 218--C 219--C 220--C 221--C 222--C 223--C 224--C 225--C 226--C 227--C 228--C 229--C 230--C 231--C 232--C 233--C 234--C 235--C 236--C 237--C 238--C 239--C 240--C 241--C 242--C
-0.752452 -0.447405 -0.537504 -0.307335 -0.019275 0.407213 -0.666976 0.319639 -0.450747 -0.197372 -0.247410 -0.644115 0.267128 -0.379032 -0.240242 -0.753454 -0.364616 -0.784357 -0.065541 -1.047176 -0.389935 -0.646241 -0.448688 -0.274207 0.107559 0.065229 -0.771804 -0.461638 -0.369913 0.078596 -1.020166 -0.457870 -0.728460 -0.380402 -0.879278 0.044452 -0.595089 -0.990054 -0.147925 -0.806377 -0.718580 -0.699646 1.762189 -0.498581 0.208342 -1.003470 -0.740667 -0.331241 -0.560938 -0.602584 -0.516947 -0.712449 -0.782752
A-6
The Impact of Derivatives on Firm Value
243--C 244--C 245--C 246--C 247--C 248--C 249--C 250--C 251--C 252--C 253--C 254--C 255--C 256--C 257--C 258--C 259--C 260--C 261--C 262--C 263--C 264--C 265--C 266--C 267--C 268--C 269--C 270--C 271--C 272--C 273--C 274--C 275--C 276--C 277--C 278--C 279--C 280--C 281--C 282--C 283--C 284--C 285--C 286--C 287--C 288--C 289--C 290--C 291--C 292--C 293--C 294--C 295--C
-0.676290 -0.315631 0.627902 -0.322376 -0.972990 -0.728781 -0.621609 -0.790601 -0.959913 -0.729204 -0.025211 -0.187031 -0.475599 -0.500342 -0.995594 0.095173 -0.954220 -0.532140 -0.606273 -0.563906 -0.297057 -0.394075 -0.499422 -0.395952 -0.928782 -0.832072 -0.399136 1.665149 -0.622900 -0.673843 -0.392805 0.633924 0.083287 -0.792756 -0.669045 1.825006 -0.564215 -0.502314 -0.921908 -0.431008 -0.773042 0.064309 -0.803729 -0.545550 -0.549413 -0.680543 0.218466 -0.714958 -0.227884 -0.393114 -0.719318 -0.725600 -0.688328
A-7
The Impact of Derivatives on Firm Value
296--C 297--C 298--C 299--C 300--C
-0.460292 -0.868783 -1.049521 0.255122 -1.012892 Effects Specification
Cross-section fixed (dummy variables) R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.857860 0.783783 0.497561 146.3120 -459.5507 11.58074 0.000000 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat 0.863412 1.070044 1.707890 3.356713 2.337752 2.729316
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The Impact of Derivatives on Firm Value
Appendix 3: Random Effect
Dependent Variable: TOBINSQ? Method: Pooled EGLS (Cross-section random effects) Date: 03/01/11 Time: 18:49 Sample: 2007 2009 Included observations: 3 Cross-sections included: 300 Total pool (balanced) observations: 900 Swamy and Arora estimator of component variances Variable C INTDERIVATIVES? COMDERIVATIVES? CURDERIVATIVES? SIZE? LEVERAGE? ROA? ROE? INVESGROWTH? DPS? Random Effects (Cross) 1--C 2--C 3--C 4--C 5--C 6--C 7--C 8--C 9--C 10--C 11--C 12--C 13--C 14--C 15--C 16--C 17--C 18--C 19--C 20--C 21--C 22--C 23--C 24--C 25--C 26--C 27--C 28--C Coefficient 2.140348 -0.038449 -0.000506 -0.084614 -0.162597 0.023077 2.110258 -0.017187 -0.163891 1.104780 Std. Error 0.521649 0.095776 0.059419 0.076579 0.057953 0.019235 0.288876 0.175262 0.040446 0.141088 t-Statistic 4.103044 -0.401447 -0.008518 -1.104929 -2.805685 1.199733 7.305075 -0.098062 -4.052077 7.830450 Prob. 0.0000 0.6882 0.9932 0.2695 0.0051 0.2306 0.0000 0.9219 0.0001 0.0000
0.311254 0.322072 0.364946 -0.044834 0.494957 0.061310 1.115054 0.555165 0.452285 0.413031 0.014232 0.135121 3.875115 0.075729 -0.132118 1.491621 0.066211 3.531785 -0.571820 -0.060569 -0.285849 -0.129019 0.094648 0.440103 0.135427 -0.161409 1.321489 -0.054302 A-9
The Impact of Derivatives on Firm Value
29--C 30--C 31--C 32--C 33--C 34--C 35--C 36--C 37--C 38--C 39--C 40--C 41--C 42--C 43--C 44--C 45--C 46--C 47--C 48--C 49--C 50--C 51--C 52--C 53--C 54--C 55--C 56--C 57--C 58--C 59--C 60--C 61--C 62--C 63--C 64--C 65--C 66--C 67--C 68--C 69--C 70--C 71--C 72--C 73--C 74--C 75--C 76--C 77--C 78--C 79--C 80--C 81--C
0.047974 1.245901 0.729868 -0.172387 -0.352946 0.743936 -0.675588 -0.066785 -0.379489 -0.276894 1.499833 0.108602 0.800861 -0.563678 -0.259531 -0.221306 0.140497 -0.191708 -0.778597 0.766400 -0.294066 -0.544681 -0.262472 -0.336806 -0.010441 0.409532 -0.215624 0.242950 0.613819 1.473131 -0.060171 1.732958 -0.424247 0.036629 0.605059 0.769380 0.016111 1.140556 0.610549 0.102151 1.326156 0.314060 0.362008 0.041730 1.390021 0.780817 0.395938 0.465403 0.440384 0.266515 0.199272 2.124273 0.771599 A-10
The Impact of Derivatives on Firm Value
82--C 83--C 84--C 85--C 86--C 87--C 88--C 89--C 90--C 91--C 92--C 93--C 94--C 95--C 96--C 97--C 98--C 99--C 100--C 101--C 102--C 103--C 104--C 105--C 106--C 107--C 108--C 109--C 110--C 111--C 112--C 113--C 114--C 115--C 116--C 117--C 118--C 119--C 120--C 121--C 122--C 123--C 124--C 125--C 126--C 127--C 128--C 129--C 130--C 131--C 132--C 133--C 134--C
0.966659 0.285123 0.130025 0.137558 -0.197766 -0.096499 3.120912 0.466255 0.276826 0.551145 -0.224216 0.230851 -0.008401 0.467668 0.062354 0.514802 0.582128 -0.002468 0.673211 0.684898 0.032217 0.238878 0.134824 0.755811 0.894520 0.255555 0.090038 0.456292 -0.032950 -0.100113 1.587289 0.589604 0.478073 0.420072 0.368225 1.127364 -0.446048 0.128693 0.907737 -0.185230 -0.057301 0.065438 -0.179873 -0.198579 -0.373722 -0.156274 -0.529064 -0.032692 -0.025527 -0.404927 -0.360689 -0.109004 -0.614930 A-11
The Impact of Derivatives on Firm Value
135--C 136--C 137--C 138--C 139--C 140--C 141--C 142--C 143--C 144--C 145--C 146--C 147--C 148--C 149--C 150--C 151--C 152--C 153--C 154--C 155--C 156--C 157--C 158--C 159--C 160--C 161--C 162--C 163--C 164--C 165--C 166--C 167--C 168--C 169--C 170--C 171--C 172--C 173--C 174--C 175--C 176--C 177--C 178--C 179--C 180--C 181--C 182--C 183--C 184--C 185--C 186--C 187--C
-0.485634 0.082016 -0.558596 -0.129232 -0.247248 0.193347 -0.755596 -0.309617 -0.483759 0.404441 -0.029039 -0.411072 0.698865 0.737446 0.336541 -0.787918 -0.288598 -0.675739 -0.409079 0.413411 0.120313 -0.402707 0.003425 0.526791 -0.114078 1.431381 -0.452609 -0.290879 -0.326266 -0.518227 -0.651611 -0.810491 -0.339580 0.296811 -0.240750 -0.104518 -1.060802 -0.310676 0.289933 -0.730357 -0.409113 0.245272 -0.640560 -0.207544 -0.032968 -0.543389 0.086429 0.668291 -0.085389 -0.715069 -0.435109 -0.193066 -0.301756 A-12
The Impact of Derivatives on Firm Value
188--C 189--C 190--C 191--C 192--C 193--C 194--C 195--C 196--C 197--C 198--C 199--C 200--C 201--C 202--C 203--C 204--C 205--C 206--C 207--C 208--C 209--C 210--C 211--C 212--C 213--C 214--C 215--C 216--C 217--C 218--C 219--C 220--C 221--C 222--C 223--C 224--C 225--C 226--C 227--C 228--C 229--C 230--C 231--C 232--C 233--C 234--C 235--C 236--C 237--C 238--C 239--C 240--C
-0.568220 -0.060373 -0.597850 -0.443565 -0.320869 -0.406533 0.106080 0.261031 -0.507544 0.183375 -0.541435 -0.119403 -0.226681 -0.635571 0.100866 -0.397147 -0.260167 -0.596005 -0.169752 -0.594734 -0.225263 -0.781463 -0.219342 -0.409492 -0.411928 -0.191529 0.072010 0.251908 -0.582210 -0.411247 -0.369527 -0.020186 -0.773694 -0.335504 -0.551342 -0.333941 -0.717805 -0.079165 -0.434587 -0.752317 -0.004802 -0.842688 -0.753515 -0.593562 1.382729 -0.338059 0.252212 -0.882727 -0.583308 -0.198641 -0.443601 -0.535815 -0.357195 A-13
The Impact of Derivatives on Firm Value
241--C 242--C 243--C 244--C 245--C 246--C 247--C 248--C 249--C 250--C 251--C 252--C 253--C 254--C 255--C 256--C 257--C 258--C 259--C 260--C 261--C 262--C 263--C 264--C 265--C 266--C 267--C 268--C 269--C 270--C 271--C 272--C 273--C 274--C 275--C 276--C 277--C 278--C 279--C 280--C 281--C 282--C 283--C 284--C 285--C 286--C 287--C 288--C 289--C 290--C 291--C 292--C 293--C
-0.443328 -0.485546 -0.599012 -0.228617 0.665572 -0.318975 -0.721582 -0.505645 -0.397068 -0.588341 -0.564128 -0.463018 0.376241 -0.158865 -0.399923 -0.301952 -0.622614 0.255140 -0.689710 -0.359838 -0.493754 -0.423549 -0.263155 -0.373384 -0.326659 -0.215785 -0.646957 -0.630597 -0.312189 1.485541 -0.492894 -0.451038 -0.425832 0.712050 0.031178 -0.520961 -0.517702 1.704332 -0.526201 -0.507154 -0.799845 -0.463540 -0.562513 -0.042638 -0.665719 -0.361270 -0.370416 -0.610728 0.153061 -0.557896 -0.069529 -0.220445 -0.630144 A-14
The Impact of Derivatives on Firm Value
294--C 295--C 296--C 297--C 298--C 299--C 300--C
-0.556228 -0.551743 -0.327792 -0.344366 -0.817212 0.203058 -0.538018 Effects Specification S.D. Rho 0.6324 0.3676
Cross-section random Idiosyncratic random Weighted Statistics R-squared Adjusted R-squared S.E. of regression F-statistic Prob(F-statistic) 0.209055 0.201057 0.525530 26.13744 0.000000
0.652601 0.497561
Mean dependent var S.D. dependent var Sum squared resid Durbin-Watson stat
0.347853 0.587949 245.8016 1.757847
Unweighted Statistics R-squared Sum squared resid 0.312392 707.7890 Mean dependent var Durbin-Watson stat 0.863412 0.610467
A-15
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