Description
The purpose of this study is to analyze the relationship between country risk, stock prices
and the exchange rate of the renminbi (RMB) compared to that of the US dollar.
Journal of Financial Economic Policy
Country risk, stock prices, and the exchange rate of the renminbi
Muhammad Umar Gang Sun
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To cite this document:
Muhammad Umar Gang Sun , (2015),"Country risk, stock prices, and the exchange rate of the
renminbi", J ournal of Financial Economic Policy, Vol. 7 Iss 4 pp. 366 - 376
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Country risk, stock prices, and
the exchange rate of the
renminbi
Muhammad Umar and Gang Sun
School of Finance, Dongbei University of Finance & Economics,
Dalian, China
Abstract
Purpose – The purpose of this study is to analyze the relationship between country risk, stock prices
and the exchange rate of the renminbi (RMB) compared to that of the US dollar.
Design/methodology/approach – An extended open macroeconomic model with investment–
saving, liquidity preference–money supply and aggregate supply functions was used by applying
comparative static analysis. After checking the series for stationarity and cointegration, a vector
autoregressive model was applied. Lag length was selected based on the Akaike information criterion,
and the coeffcients were calculated for the overall sample and for pre- and post-July 2005 periods.
Findings – The stock market index is a signifcant determinant of variation in the exchange rate: when
the Chinese stock market performs well, the RMB appreciates and vice versa. Country risk is not a
signifcant determinant of the exchange rate, but the exchange rate of the RMB is a highly signifcant
determinant of the country risk of China: depreciation of the RMBresults in higher country risk and vice
versa.
Research limitations/implications – Linear interpolation was used to calculate the monthly
values of some of the variables for which only annual data were available.
Practical implications – The authorities should revalue the exchange rate of the RMB against the
US dollar, which will result in lower country risk for China. One way to achieve this is to strengthen the
performance of stock markets.
Originality/value – To the best of the authors’ knowledge, this is the frst study to explore the
relationship between the country risk of China and the exchange rate of the RMB. Using an open
macroeconomic model, this novel research analyzes the relationships between country risk, stock prices
and the exchange rate of the RMB from a different perspective.
Keywords Foreign exchange, Chinese stock market
Paper type Research paper
1. Introduction
A foreign “exchange rate” is defned as the value of one currency in terms of another.
The exchange rate of the renminbi (RMB; also referred to as the Chinese yuan) is a
much-discussed topic, with research undertaken concerning it from a number of
different points of views. Most of the focus is on fnding the equilibrium exchange rate
of the RMB and exploring the effect of regime changes on the exchange rate of the
Chinese yuan. Researchers seemto agree that the RMB has been kept undervalued over
a long period to promote exports and hence growth. However, other studies, exploring
the relationship between stock prices and the exchange rate, have reached different
JEL classifcation – F31, F41, G01
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1757-6385.htm
JFEP
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Received27 November 2014
Revised26 May2015
9 June 2015
29 June 2015
Accepted6 July2015
Journal of Financial Economic
Policy
Vol. 7 No. 4, 2015
pp. 366-376
©Emerald Group Publishing Limited
1757-6385
DOI 10.1108/JFEP-11-2014-0073
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conclusions. Abrief overviewof all of these studies is presented in the literature review
section of the present paper.
“Country risk” is the likelihood that a country will be unable or unwilling to repay its
debt. This, too, has emerged as a hot topic for analysis, particularly following the
fnancial crisis of 2007-08. According to Heinrichs and Stanoeva (2012), countries such
as Portugal, Ireland, Italy, Greece and Spain – commonly known as “PIIGS” – were
supposed to have a low country risk before the crisis, but ranked higher on the scale
afterwards. Similarly, countries such as Brazil, Russia, India, China and South Africa
(“BRICS”) were considered to have a high country risk before the crisis, but currently
they rank comparatively low. Because of the increased importance of country risk,
researchers have begun to explore the relationship of country risk with the exchange
rate of different countries. Some consider that exchange rate affects country risk, while
others argue the opposite.
A“stock market index” represents the performance of a particular stock market, but
is also thought to be indicative of the economic performance of a country. It has become
an area of interest for many as a result of the increased international capital fows
following the abolition of capital controls, particularly during the 1980s. Since then, a lot
of research has been undertaken that explores the relationship between stock market
movements and exchange rates, with some scholars believing that there is a causal
relationship between the two and others disagreeing. Several researchers believe that
the “portfolio balance effect” theory holds, but others do not. Thus, there are conficting
point of views regarding the relationship between stock prices and an exchange rate.
The present study analyzes the relationship between the country risk of China, one of
its stock market indices, and the exchange rate of the RMB through use of an extended
open macroeconomic model. To the best of the authors’ knowledge, none of the existing
literature explores the relationship between the country risk of China and the exchange
rate of the RMB. This study attempts to bridge that gap, and it does so by utilizing an
extended open macroeconomic model to explore the relationship between these
variables froma different perspective. Its fndings will help scholars and policy-makers
to understand how country risk and exchange rate are related in the case of China, as
well as determine the relationship between the stock market and the exchange rate of
RMB. The study’s results also help to elucidate the relationship between the stock
market and the country risk of China.
2. Literature review
This study relates three different strands of the current literature:
(1) studies exploring the equilibrium exchange rate of the RMB;
(2) research on the relationship between country risk and exchange rate; and
(3) analyses related to the relationship between the stock market and the exchange
rate.
Many academics have sought to fnd the equilibriumexchange rate of the RMB and the
relationship between stock prices and the exchange rate. However, comparatively little
research has been undertaken on the relationship between country risk and the
exchange rate. A summary and comparison of prior studies is given below.
Chou and Shih (1998) found that the actual rate of the RMB was overvalued,
compared to the equilibrium rate, and the government maintained the exchange rate
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Exchange rate
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near to the equilibrium rate from 1990 to 1994, which, according to purchasing power
parity theorizing, was undervalued. Conversely, Zhang and Pan (2004) observed that the
RMB exchange rate was undervalued, and that it may have appreciated by 15-22 per
cent in 2013, from 1996, in the absence of government intervention. An important point
to note is that the data used by Chou and Shih (1998) range fromthe frst quarter of 1981
to the last quarter of 1994, whereas the data used by Zhang and Pan (2004) range from
1996 to 2000. Reviewing the history of exchange rate regimes adopted by China, Huang
and Wang (2004) concluded that the government should be very careful in adopting the
newexchange rate regime because of weak economic fundamentals, less liquid fnancial
markets and fragile fnancial institutions. A later study conducted by Goldstein and
Lardy (2006) supported those fndings, noting that it would be hard for the Chinese
Government to switch to another regime of exchange rate due to the feeble banking
system, the extent of RMB undervaluation and the possible reduction in export and
higher unemployment. They suggested that the government should immediately
revalue the currency from 10 to 15 per cent and widen the fuctuation band from 5 to 7
per cent. They also proposed that the government should adopt a loose fscal policy to
overcome the adverse effects of aforementioned moves. As far as the determinants of the
RMB exchange rate are concerned, Wang (2005) found that real demand and supply
shocks explain most of the changes in the real exchange rate. The same study also noted
that nominal supply and demand shocks are equally important.
Regarding the relationship between exchange rate and country risk, Kuttner and
Mosser (2002) proposed that a higher country risk could reduce investment spending,
decrease money demand and affect the real exchange rate. Specifcally, they suggested
that a higher stock value might affect the real exchange rate via a wealth effect on
consumption and a balance-sheet effect on investment. Hsing (2008) found that the real
exchange rate in Singapore was negatively related to country risk and positively to
stock prices. He also perceived that government spending was an insignifcant
determinant of real exchange rate. On the other hand, Bordo et al. (2009) explored the
effect of exchange rate fuctuations on country risk and learned that exchange rate
depreciation results in higher sovereign risk if the country is supposed to repay external
debt.
Several studies have been conducted that explore the relationship between exchange
rates and stock prices. Some of them explore the relationship between the two series in
pre- and post-crisis periods, while others focus on the short-term and long-term
relationships; some focus on developed countries, and others on developing and
emerging countries. At times, the inferences of these studies can appear contradictory.
For instance, Nieh and Lee (2001) did not discover any relationship between stock prices
and exchange rates for G7 countries in the long run. However, they did perceive a
short-termrelationship (of only one day) for certain G7 countries. On the other hand, Pan
et al. (2007) found a signifcant causal relationship between stock prices and exchange
rates for Hong Kong, Japan, Malaysia and Thailand before the 1997 Asian fnancial
crisis. Moreover, although none of the countries showed signifcant causality between
stock prices and exchange rates during the 1997 crisis, all except Malaysia showed a
relationship between exchange rates and stock prices. Thus, their fndings run counter
to the portfolio balance effect theory for six out of seven East Asian countries. As far as
the relationship between exchange rate and stock prices in China is concerned, Zhao
(2010) did not fnd any stable long-term equilibrium relationship between the real
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effective exchange rate and stock prices. He concluded that past innovation in a stock
market affects future volatility in an exchange market and vice versa. Conversely, Cao
et al. (2012) discovered that the cross-correlation between the Chinese exchange market
and its stock market varies with time and is sensitive to the RMB exchange rate regime.
Meanwhile, the fndings of Chkili et al. (2012), suggesting that there is a signifcant
bilateral relationship between the stock and exchange markets for France and Germany,
are consistent with those of Pan et al. (2007). In another study, Chkili and Nguyen (2014)
noticed that the stock market has more infuence on exchange rates in both calm and
turbulent periods for BRICS countries.
This literature reviewillustrates that a lot of research has been carried out exploring
the relationship between exchange rates and stock markets and fnding the equilibrium
exchange rate for the RMB, but comparatively little has been done to assess the
relationship between country risk and the exchange rate of the RMB. Accordingly, the
present study explores the impact of country risk and stock prices on the exchange rate
of the RMB to bridge this gap.
3. Extended open macroeconomic model
Following Hsing (2008), this study uses an extended open macroeconomic model to
ascertain the relationships between country risk, stock prices and the exchange rate of
the RMB. According to this model, aggregate spending is a function of real output, real
interest rate, government spending, government revenue, real exchange rate, stock
prices and world output. Real money demanded is a function of nominal interest rate
stock prices and real output. Infation rate is infuenced by expected infation rate and
the difference between actual and potential output. Hence, the open macroeconomic
model for China is presented as:
Y ? E(Y, R ? X ? ?
e
, G, T, ?, S, Y
*
)
M ? L
(
R ? X, Y, S
)
? ? ?
e
? A(Y ? Y
n
)
where Ystands for real GDP; E, aggregate expenditure; (R?X??
e
), real interest rate;
R, world interest rate; X, country risk; ?
e
, expected infation; G, government spending;
T, government tax revenue; ? , real exchange rate; S, stock index; Y*, world output; M,
money supply; L, real demand for money; ? , infation rate; and Y
N
, potential output.
Let:
E
Y
? 0, E
R?X??e
? 0, E
G
? 0, E
T
? 0, E
?
? 0, E
S
? 0, E
Y*
? 0, L
R?X
? 0,
L
Y
? 0, L
S
? or ? 0, ?
Y
? A?0
Solving for the three unknowns – Y, ? and ?– by applying the implicit function theorem,
the equilibrium exchange rate of RMB can be expressed as:
? ? ?(M, G, T, S, X, R, ?
e
, Y
*
;?, A, Y
N
)
369
Exchange rate
of the
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According to the above model, a higher stock price would be expected to increase the
exchange rate if the demand for money has a positive relationship with the stock price.
Mathematically, this is represented as:
??
?S
?
L
S
(1 ? E
Y
) ? L
Y
E
S
?
J
?
? 0 If L
S
? 0
On the other hand, a higher country risk would be expected to result in a lower ? .
Mathematically, this is expressed as:
??
?X
?
L
X
(1 ? E
Y
) ? L
Y
E
X
?
J
?
? 0
where:
?
J
?
? ?L
Y
E
?
? 0
4. Methodology
4.1 Sample
To ascertain the relationship between country risk, stock market index and the
exchange rate of the RMB, data were been obtained froma number of sources, including
the International Monetary Fund’s International Financial Statistics and the Economist
Intelligence Unit’s Country data. The study period was fromJanuary 2000 to December
2013, representing 168 observations in total. Annual data regarding country risk and
exchange rate were converted into monthly data using linear interpolation. To calculate
the monthly values, the yearly value was deemed the year-end value.
4.2 Variables
Our sample included data concerning four different variables: the nominal exchange
rate of the RMB, the country risk of China, the Shanghai Stock Exchange (SSE)
composite index and a dummy variable. The exchange rate of the RMB is a direct quote
(i.e. the value of the RMB per US dollar). Thus, an increase in the value means a
depreciation of the RMB and vice versa.
The average interest rate on newexternal debt commitments was used as a proxy for
the country risk of China. Higher interest rates mean a high risk of default and vice
versa. The interest rate on external debt represents the average interest rate on all new
public and publically guaranteed loans contracted during the year. To obtain the
average, the interest rates for all public and publically guaranteed loans were weighted
by the amounts of the loans. The causality of the relationship between the exchange rate
of the RMB and country risk is ambiguous; Bordo et al. (2009) identifed that changes in
the exchange rate caused fuctuations in country risk, yet Hsing (2008) found the
opposite to be the case.
The Chinese stock market was represented by the SSE’s “A” share price index. All
monthly values were end-of-the-period values. Note that the relationship between the stock
market and exchange rates is ambiguous, too, with studies publishing dissimilar fndings.
Adummy variable (“D05”) was used to capture the effect of regime change. Its value
was designated as “1” from July 2005 onwards, and “0” prior to that date. In 2005, the
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Chinese authorities decided to value the exchange rate of the RMB in reference to a
basket of currencies rather than against the US dollar alone.
5. Descriptive statistics and correlation matrix
Tables I and II present the descriptive statistics and the correlation matrix of the study’s
variables. The average value of the RMB per US dollar was 6.196 over the study period,
with a standard deviation of 78 per cent. The series was negatively skewed and had a
platykurtic distribution. The average interest rate on external debt commitments was
4.135 per cent. This series was also negatively skewed, and the distribution was near
normal. The average value of the SSEAshare price index was 2,319.35, with a very high
standard deviation of 945.223. This series was positively skewed and leptokurtic, which
means that it included extreme values as well.
The correlation matrix presented in Table II suggests that there is positive
correlation between the country risk of China and the exchange rate of the RMB. This
means that, when the RMB depreciates, the value of the country risk increases and vice
versa. The correlation between the stock market and the exchange rate is shown to be
negative, which means that, when Chinese stock market performs well, the value of the
RMB appreciates and vice versa. Table II illustrates that the exchange rate of the RMB
appreciated after the exchange rate regime change in 2005. The correlation between
regime change and country risk is negative, while it is positive for the stock market. This
means that the country risk of China decreased after 2005, and the performance of the
stock market improved afterwards.
Table I.
Descriptive statistics
N Mean Minimum Maximum SD Skewness Kurtosis
ER 168 7.545 6.196 8.279 0.784 ?0.439 1.494
CR 168 4.135 1.538 6.222 1.194 ?0.174 2.235
SMI 168 2,319.355 1,113.290 6,251.530 945.223 1.613 6.289
D05 168 0.607 0.000 1.000 0.490 ?0.439 1.193
Notes: Table I reports the summary statistics of the nominal exchange rate of the RMB per US dollar
(ER); the average interest rate on new external debt commitments, used as a proxy for the country risk
(CR); SSE A share price index (SMI); and a dummy variable representing the shift in the exchange rate
regime in 2005 (D05)
Table II.
Correlation matrix
ER CR SMI D05
ER 1
CR 0.751*** (0.000) 1
SMI ?0.385*** (0.000) ?0.016 (0.842) 1
D05 ?0.751*** (0.000) ?0.470*** (0.000) 0.527*** (0.000) 1
Notes: Table II reports the pair-wise correlation matrix of the series used in this study’s analysis;
parentheses denote p values, and *, ** and ***represent levels of statistical signifcance at 10, 5 and
1% levels, respectively; see Table I for defnitions of the ER, CR, SMI and D05 variables
371
Exchange rate
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6. Econometric model
To determine the relationships between country risk, the stock market and the exchange
rate of the RMB, we checked all of the series for stationarity by using an augmented
Dickey–Fuller test with 13 lags. We calculated lag length based on Schwert’s rule of
thumb:
P
max
?
?
12 ·
(
T
100
)
1
4
?
where T is the number of observations. We were unable to reject the null hypothesis of
the unit root for all of the series. To ascertain the level of integration, we applied the
Dickey–Fuller test on the frst and second differences of the series and found that the
stock market index was integrated at the frst order, and the other two series were
integrated at the second order. Table III presents the results of the augmented Dickey–
Fuller test.
As the exchange rate and country risk were perceived to be integrated at the same
order, a Johansen test for cointegration was used to identify the cointegration between
them. This test revealed that there is no cointegration between the exchange rate and
country risk of China.
Therefore, as the three series were shown not to be cointegrated, a vector
autoregressive (VAR) model was utilized to explore the relationships between them. The
following set of equations represents the VAR model:
X
t
? ?
10
? ?
11
X
t?2
? ?
12
Y
t?2
? ?
13
Z
t?2
? ?
14
D
t?2
? ?
12
Y
t
? ?
20
? ?
21
X
t?2
? ?
22
Y
t?2
? ?
23
Z
t?2
? ?
24
D
t?2
? ?
22
Z
t
? ?
30
? ?
31
X
t?2
? ?
32
Y
t?2
? ?
33
Z
t?2
? ?
34
D
t?2
? ?
32
D
t
? ?
40
? ?
41
X
t?2
? ?
42
Y
t?2
? ?
43
Z
t?2
? ?
44
D
t?2
? ?
42
where Xstands for exchange rate, Yfor country risk, Z for stock market index and Dfor
the dummy variable. The subscripted t represents time and t-2 represents the second
lag. ? represents the intercept for each equation and ?,?,? and ? represent the slope
coeffcients of exchange rate, country risk, stock prices and the dummy variable,
respectively. ? represents the error term. The lag length of two was selected based on
factor price equalization, the Akaike information criterion, the Hannan–Quinn
information criterion and Schwarz’s Bayesian information criterion.
Table III.
Augmented Dickey–
Fuller test for unit
roots
Variable
Test in level Test in frst difference Test in second difference
No. of trend Trend No. of trend Trend No. of trend Trend
ER ?0.303 ?2.467 ?1.936 ?1.921 ?3.702* ?3.737*
CR ?1.733 ?3.195 ?2.68 ?2.661 ?4.292* ?4.273*
SMI ?1.753 ?1.884 ?5.441* ?5.441*
Notes: Based on Schwert’s rule of thumb, the lag length for all the series is 13; *denotes stationarity;
See Table I for defnitions of the ER, CR and SMI variables
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7. Empirical fndings
Table IV presents the relationships found between the exchange rate, country risk and
the stock market for the whole sample, while Tables Vand VI details these relationships
before and after the regime change of 2005, respectively. All coeffcients represent the
relationships between the second lag of the independent variable and the dependent
variable. According to these results, country risk is not a signifcant determinant of the
exchange rate of the RMB, but the stock market is. The relationship between the stock
Table IV.
Relationship between
the exchange rate,
country risk and the
stock market index
for overall sample
Dependent variables
ER CR SMI D05
ER 0.989*** (232.530) 0.104*** (3.030) 48.613 (0.700) 0.016 (0.690)
CR ?0.002 (?0.910) 0.965*** (55.220) 55.743 (1.570) ?0.013 (?1.070)
SMI ?1.1E-05*** (?5.380) ?3.3E-05** (?1.960) 0.868*** (25.410) ?5.82E-06 (?0.510)
D05 ?0.043*** (?8.370) 0.131*** (3.160) 293.780*** (3.490) 0.980*** (35.040)
CONS. 0.122*** (4.090) ?0.680*** (?2.840) ?463.682 (?0.950) ?0.031 (?0.190)
Notes: Table IVrepresents the relationship between the exchange rate of the RMB, the country risk of
China, the SSE A share stock index and a dummy variable representing the exchange rate regime
change in 2005; parentheses denote z values, and *, **and ***represent statistical signifcance at 10,
5 and 1% levels, respectively; see Table I for defnitions of the ER, CR, SMI and D05 variables
Table V.
Relationship between
the exchange rate,
country risk and the
stock market index
before July 2005
Dependent variables
ER CR SMI
ER 1.585*** (23.490) ?11.964*** (?2.660) 8,697.958** (2.330)
CR 0.00005 (0.110) 0.954*** (35.050) 54.150** (2.390)
SMI 1.3E-06 (0.800) 0.000235** (2.170) 0.732688*** (8.120)
CONS. ?4.842*** (?8.690) 98.785*** (2.660) ?71,808.9** (?2.320)
Notes: Table V reports the relationship between the exchange rate of the RMB, the country risk of
China and the stock market index before the exchange rate regime change in 2005; parentheses denote
z values, and *, **and ***represent statistical signifcance at 10, 5 and 1% levels, respectively; see
Table I for defnitions of the ER, CR and SMI variables
Table VI.
Relationship between
the exchange rate,
country risk and the
stock market index
after July 2005
Dependent variables
ER CR SMI
ER 1.0171*** (90.57) 0.3588*** (4.83) ?87.0766 (?0.49)
CR ?0.0289*** (?3.98) 0.7996*** (16.65) 198.2458* (1.72)
SMI ?0.00001*** (?3.61) ?0.00002 (?0.79) 0.7533*** (12.60)
CONS. ?0.0378 (?0.61) ?1.8004*** (?4.41) 586.8742 (0.60)
Notes: Table VI reports the relationship between the exchange rate of the RMB, the country risk of
China and the stock market index after the exchange rate regime change in 2005; parentheses denote z
values, and *, ** and ***represent statistical signifcance at 10, 5 and 1% levels, respectively; see
Table I for defnitions of the ER, CR and SMI variables
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market and the exchange rate is negative, which means that, when the Chinese stock
market performs well, the value of the RMB appreciates. The coeffcient of the dummy
variable illustrates that the value of the RMB appreciated after the regime change.
Interestingly, the results of the second equation reveal that exchange rate is a highly
signifcant determinant of country risk in the case of China, and a depreciation of the
exchange rate results in a higher country risk. This fnding is in accordance with that of
Bordo et al. (2009). The last column of Table IV illustrates that none of the three
variables explain the variation following regime change.
The results of a Granger-causality Wald test reveal that, in the case of China, country
risk does not Granger-cause the exchange rate, but the stock market and regime changes
do. On the other hand, the exchange rate Granger-causes country risk. This fnding is in
accordance with that of Tsagkanos and Siriopoulos (2013), who discovered that, in the
case of the USA, the exchange rate Granger-causes country risk in the short term. The
country risk of China is also caused by the stock market and regime shift. Interestingly,
neither the exchange rate nor country risk Granger-causes stock prices, but the stock
market Granger-causes both the exchange rate and country risk. Furthermore, a shift in
the exchange rate regime Granger-causes stock market variations. This study’s fndings
regarding regime change are in accordance with those of Cao et al. (2012).
To get an understanding of the effect of regime change on the relationship between
country risk, stock prices and the exchange rate, the study’s sample was divided into
two parts: pre- and post-2005. In July 2005, the authorities in China decided to calculate
the value of the RMBwith reference to a basket of currencies rather than simply against
the US dollar. The present study’s results presented in Table V reveal that neither
country risk nor the stock index used were signifcant determinants of variation in the
nominal exchange rate of the RMB prior to the exchange rate regime change in 2005.
However, the exchange rate and the stock market index used were signifcant
determinants of country risk in the previous regime. Surprisingly, depreciation of the
RMB was associated with lower country risk, and better performance of the stock
market was associated with higher country risk for China. On the other hand,
depreciation of the exchange rate was associated with better performance of stock
market, and higher country risk was also associated with a better performance of the
stock market. The results of the Granger-causality Wald test suggest that neither
country risk nor the stock market used Granger-caused the exchange rate of the RMBin
the previous regime. However, the exchange rate used did Granger-cause country risk.
Thus, the causality was fromexchange rate to country risk. The stock market index was
Granger-caused by the exchange rate as well as country risk.
Table VI represents the relationship between the exchange rate, country risk and
stock market in the study period after the regime change in 2005. All of the results for
this period are based on three lags, as suggested by the Akaike information criterion.
Table VI shows that, in this post-regime change period, both country risk and the stock
market are signifcant determinants of the exchange rate of the RMB. An increase in
country risk is associated with an appreciation of the exchange rate, and a better
performance of the stock market results in an appreciation of the exchange rate as well.
In this period, the exchange rate is also a signifcant determinant of country risk, which
means that a depreciation of the exchange rate results in a higher country risk.
Interestingly, in this period, neither country risk nor the exchange rate determines a
variation in stock prices. A Granger-causality Wald test reveals that both country risk
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and stock index Granger-cause the exchange rate. On the other hand, the exchange rate
also causes country risk, but the stock market index does not. Furthermore, neither
exchange rate nor country risk Granger-cause stock market movements.
So, according to these results, the relationship between country risk, the exchange
rate and the stock market index changed after the regime change. Before 2005, country
risk was not a signifcant determinant of the exchange rate, and this was also true the
other way around, with the relationship between country risk and the stock market
being bidirectional. Exchange rate was a signifcant determinant of both country risk
and the stock market in the previous regime, whereas the relationship between country
risk and the exchange rate is bidirectional in the current regime. Variation in the stock
market explains the variation in the exchange rate, but neither country risk nor the
exchange rate explains variation in the stock market index.
8. Conclusion
This study’s results regarding the short-term relationship between country risk, stock
prices and the exchange rate reveals that, in the case of China, exchange rate
Granger-causes country risk, but not the other way around. Similarly, the stock market
index Granger-causes exchange rate, but the reverse is not true. The relationship
between country risk and the stock market index is also unidirectional (i.e. from stock
market to country risk). Thus, the variation in country risk is explained by both the
exchange rate and stock prices, but the variation in the exchange rate is only explained
by the stock market index. Variation in the stock market index is explained by neither
the exchange rate nor country risk.
These fndings suggest that a better performance of the stock market results into the
appreciation of the RMB. This may be because of the portfolio investment fowing into
the stock markets of the country, as a result of which demand for the RMBincreases and,
in turn, the RMB appreciates. Furthermore, a better performance of the stock market is
shown to be linked with lower country risk, which increases when the RMBdepreciates.
This fnding is in accordance with that of Bordo et al. (2009), who found that exchange
rate depreciation results in a higher sovereign risk if the country in question is exposed
to foreign country debt.
Based on this study’s results, it is proposed that the authorities in China should
revalue the exchange rate of the RMB. The degree of revaluation should be around 15
per cent, as suggested by Zhang and Pan (2004) and Goldstein and Lardy (2006). Such a
revaluation will result in lower country risk, which in turn will bring about lower
interest on new external debt commitments for the government. The authorities could
achieve this goal of revaluation by improving the stock markets and attracting more
portfolio investment, because, according to the study’s results, if the stock market
performs better, the value of the RMB appreciates. Secondly, better stock markets will
boost investment, which will result in higher investment and lower unemployment. This
approach would help the authorities to maintain the new normal model of growth.
References
Bordo, M.D., Meissner, C.M. and Weidenmier, M.D. (2009), “Identifying the effect of an exchange
rate depreciation on country risk: evidence from a natural experiment”, Journal of
International Money and Finance, Vol. 28 No. 6, pp. 1022-1044.
375
Exchange rate
of the
renminbi
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b
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2
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r
y
2
0
1
6
(
P
T
)
Cao, C., Xu, L. and Cao, J. (2012), “Multifractal detrended cross-correlations between the Chinese
exchange market and stock market”, Physica A, Vol. 391 No. 20, pp. 4855-4866.
Chkili, W., Aloui, C. and Nguyen, D.K. (2012), “Asymmetric effects and long memory in dynamic
volatility relationships between stock returns and exchange rates”, Journal of International
Financial Markets, Institutions & Money, Vol. 22 No. 4, pp. 738-757.
Chkili, W. and Nguyen, D.K. (2014), “Exchange rate movements and stock market returns in a
regime-switching environment: evidence for BRICS countries”, Research in International
Business and Finance, Vol. 31, pp. 46-56.
Chou, W.L. and Shih, Y.C. (1998), “The equilibriumexchange rate of Chinese renminbi”, Journal of
Comparative Economics, Vol. 26 No. 1, pp. 165-174.
Goldstein, M. and Lardy, N. (2006), “China’s exchange rate policy dilemma”, The American
Economic Review, Vol. 96 No. 2, pp. 422-426.
Heinrichs, M. and Stanoeva, I. (2012), “Country risk and sovereign risk: building clearer borders”,
Euromoney Risk Management Handbook, Euromoney Trading, London, pp. 15-24.
Hsing, Y. (2008), “The impacts of the stock price and country risk on the exchange rate in
Singapore”, International Journal of Development Issues, Vol. 7 No. 1, pp. 56-61.
Huang, H. and Wang, S. (2004), “Exchange rate regimes: China’s experience and choices”, China
Economic Review, Vol. 15 No. 3, pp. 336-342.
Kuttner, K.N. and Mosser, P. (2002), “The monetary transmission mechanism: some answers and
further questions”, Federal Reserve Bank of NewYork Economic Policy Review, Vol. 8 No. 1,
pp. 15-26.
Nieh, C.C. and Lee, C.F. (2001), “Dynamic relationship between stock prices and exchange rates for
G-7 countries”, The Quarterly Review of Economics and Finance, Vol. 41 No. 4, pp. 477-490.
Pan, M.S., Fok, R.C.W. and Liu, Y.A. (2007), “Dynamic linkages between exchange rates and stock
prices: evidence fromEast Asian markets”, International Reviewof Economics and Finance,
Vol. 16 No. 4, pp. 503-520.
Tsagkanos, A. and Siriopoulos, C. (2013), “Along-run relationship between stock price index and
exchange rate: a structural nonparametric cointegrating regression approach”, Journal of
International Financial Markets, Institutions & Money, Vol. 25 No. 1, pp. 106-118.
Wang, T. (2005), “Sources of real exchange rate fuctuations in China”, Journal of Comparative
Economics, Vol. 33 No. 4, pp. 753-771.
Zhang, F. and Pan, Z. (2004), “Determination of China’s long-run nominal exchange rate and
offcial intervention”, China Economic Review, Vol. 15 No. 3, pp. 360-365.
Zhao, H. (2010), “Dynamic relationship between exchange rate and stock price: evidence from
China”, Research in International Business and Finance, Vol. 24 No. 2, pp. 103-112.
Further reading
Mankiw, N.G. (2007), Macroeconomics, 6th ed., Worth, New York, NY.
Corresponding author
Gang Sun can be contacted at: [email protected]
For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
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doc_163290067.pdf
The purpose of this study is to analyze the relationship between country risk, stock prices
and the exchange rate of the renminbi (RMB) compared to that of the US dollar.
Journal of Financial Economic Policy
Country risk, stock prices, and the exchange rate of the renminbi
Muhammad Umar Gang Sun
Article information:
To cite this document:
Muhammad Umar Gang Sun , (2015),"Country risk, stock prices, and the exchange rate of the
renminbi", J ournal of Financial Economic Policy, Vol. 7 Iss 4 pp. 366 - 376
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Country risk, stock prices, and
the exchange rate of the
renminbi
Muhammad Umar and Gang Sun
School of Finance, Dongbei University of Finance & Economics,
Dalian, China
Abstract
Purpose – The purpose of this study is to analyze the relationship between country risk, stock prices
and the exchange rate of the renminbi (RMB) compared to that of the US dollar.
Design/methodology/approach – An extended open macroeconomic model with investment–
saving, liquidity preference–money supply and aggregate supply functions was used by applying
comparative static analysis. After checking the series for stationarity and cointegration, a vector
autoregressive model was applied. Lag length was selected based on the Akaike information criterion,
and the coeffcients were calculated for the overall sample and for pre- and post-July 2005 periods.
Findings – The stock market index is a signifcant determinant of variation in the exchange rate: when
the Chinese stock market performs well, the RMB appreciates and vice versa. Country risk is not a
signifcant determinant of the exchange rate, but the exchange rate of the RMB is a highly signifcant
determinant of the country risk of China: depreciation of the RMBresults in higher country risk and vice
versa.
Research limitations/implications – Linear interpolation was used to calculate the monthly
values of some of the variables for which only annual data were available.
Practical implications – The authorities should revalue the exchange rate of the RMB against the
US dollar, which will result in lower country risk for China. One way to achieve this is to strengthen the
performance of stock markets.
Originality/value – To the best of the authors’ knowledge, this is the frst study to explore the
relationship between the country risk of China and the exchange rate of the RMB. Using an open
macroeconomic model, this novel research analyzes the relationships between country risk, stock prices
and the exchange rate of the RMB from a different perspective.
Keywords Foreign exchange, Chinese stock market
Paper type Research paper
1. Introduction
A foreign “exchange rate” is defned as the value of one currency in terms of another.
The exchange rate of the renminbi (RMB; also referred to as the Chinese yuan) is a
much-discussed topic, with research undertaken concerning it from a number of
different points of views. Most of the focus is on fnding the equilibrium exchange rate
of the RMB and exploring the effect of regime changes on the exchange rate of the
Chinese yuan. Researchers seemto agree that the RMB has been kept undervalued over
a long period to promote exports and hence growth. However, other studies, exploring
the relationship between stock prices and the exchange rate, have reached different
JEL classifcation – F31, F41, G01
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1757-6385.htm
JFEP
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Received27 November 2014
Revised26 May2015
9 June 2015
29 June 2015
Accepted6 July2015
Journal of Financial Economic
Policy
Vol. 7 No. 4, 2015
pp. 366-376
©Emerald Group Publishing Limited
1757-6385
DOI 10.1108/JFEP-11-2014-0073
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conclusions. Abrief overviewof all of these studies is presented in the literature review
section of the present paper.
“Country risk” is the likelihood that a country will be unable or unwilling to repay its
debt. This, too, has emerged as a hot topic for analysis, particularly following the
fnancial crisis of 2007-08. According to Heinrichs and Stanoeva (2012), countries such
as Portugal, Ireland, Italy, Greece and Spain – commonly known as “PIIGS” – were
supposed to have a low country risk before the crisis, but ranked higher on the scale
afterwards. Similarly, countries such as Brazil, Russia, India, China and South Africa
(“BRICS”) were considered to have a high country risk before the crisis, but currently
they rank comparatively low. Because of the increased importance of country risk,
researchers have begun to explore the relationship of country risk with the exchange
rate of different countries. Some consider that exchange rate affects country risk, while
others argue the opposite.
A“stock market index” represents the performance of a particular stock market, but
is also thought to be indicative of the economic performance of a country. It has become
an area of interest for many as a result of the increased international capital fows
following the abolition of capital controls, particularly during the 1980s. Since then, a lot
of research has been undertaken that explores the relationship between stock market
movements and exchange rates, with some scholars believing that there is a causal
relationship between the two and others disagreeing. Several researchers believe that
the “portfolio balance effect” theory holds, but others do not. Thus, there are conficting
point of views regarding the relationship between stock prices and an exchange rate.
The present study analyzes the relationship between the country risk of China, one of
its stock market indices, and the exchange rate of the RMB through use of an extended
open macroeconomic model. To the best of the authors’ knowledge, none of the existing
literature explores the relationship between the country risk of China and the exchange
rate of the RMB. This study attempts to bridge that gap, and it does so by utilizing an
extended open macroeconomic model to explore the relationship between these
variables froma different perspective. Its fndings will help scholars and policy-makers
to understand how country risk and exchange rate are related in the case of China, as
well as determine the relationship between the stock market and the exchange rate of
RMB. The study’s results also help to elucidate the relationship between the stock
market and the country risk of China.
2. Literature review
This study relates three different strands of the current literature:
(1) studies exploring the equilibrium exchange rate of the RMB;
(2) research on the relationship between country risk and exchange rate; and
(3) analyses related to the relationship between the stock market and the exchange
rate.
Many academics have sought to fnd the equilibriumexchange rate of the RMB and the
relationship between stock prices and the exchange rate. However, comparatively little
research has been undertaken on the relationship between country risk and the
exchange rate. A summary and comparison of prior studies is given below.
Chou and Shih (1998) found that the actual rate of the RMB was overvalued,
compared to the equilibrium rate, and the government maintained the exchange rate
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near to the equilibrium rate from 1990 to 1994, which, according to purchasing power
parity theorizing, was undervalued. Conversely, Zhang and Pan (2004) observed that the
RMB exchange rate was undervalued, and that it may have appreciated by 15-22 per
cent in 2013, from 1996, in the absence of government intervention. An important point
to note is that the data used by Chou and Shih (1998) range fromthe frst quarter of 1981
to the last quarter of 1994, whereas the data used by Zhang and Pan (2004) range from
1996 to 2000. Reviewing the history of exchange rate regimes adopted by China, Huang
and Wang (2004) concluded that the government should be very careful in adopting the
newexchange rate regime because of weak economic fundamentals, less liquid fnancial
markets and fragile fnancial institutions. A later study conducted by Goldstein and
Lardy (2006) supported those fndings, noting that it would be hard for the Chinese
Government to switch to another regime of exchange rate due to the feeble banking
system, the extent of RMB undervaluation and the possible reduction in export and
higher unemployment. They suggested that the government should immediately
revalue the currency from 10 to 15 per cent and widen the fuctuation band from 5 to 7
per cent. They also proposed that the government should adopt a loose fscal policy to
overcome the adverse effects of aforementioned moves. As far as the determinants of the
RMB exchange rate are concerned, Wang (2005) found that real demand and supply
shocks explain most of the changes in the real exchange rate. The same study also noted
that nominal supply and demand shocks are equally important.
Regarding the relationship between exchange rate and country risk, Kuttner and
Mosser (2002) proposed that a higher country risk could reduce investment spending,
decrease money demand and affect the real exchange rate. Specifcally, they suggested
that a higher stock value might affect the real exchange rate via a wealth effect on
consumption and a balance-sheet effect on investment. Hsing (2008) found that the real
exchange rate in Singapore was negatively related to country risk and positively to
stock prices. He also perceived that government spending was an insignifcant
determinant of real exchange rate. On the other hand, Bordo et al. (2009) explored the
effect of exchange rate fuctuations on country risk and learned that exchange rate
depreciation results in higher sovereign risk if the country is supposed to repay external
debt.
Several studies have been conducted that explore the relationship between exchange
rates and stock prices. Some of them explore the relationship between the two series in
pre- and post-crisis periods, while others focus on the short-term and long-term
relationships; some focus on developed countries, and others on developing and
emerging countries. At times, the inferences of these studies can appear contradictory.
For instance, Nieh and Lee (2001) did not discover any relationship between stock prices
and exchange rates for G7 countries in the long run. However, they did perceive a
short-termrelationship (of only one day) for certain G7 countries. On the other hand, Pan
et al. (2007) found a signifcant causal relationship between stock prices and exchange
rates for Hong Kong, Japan, Malaysia and Thailand before the 1997 Asian fnancial
crisis. Moreover, although none of the countries showed signifcant causality between
stock prices and exchange rates during the 1997 crisis, all except Malaysia showed a
relationship between exchange rates and stock prices. Thus, their fndings run counter
to the portfolio balance effect theory for six out of seven East Asian countries. As far as
the relationship between exchange rate and stock prices in China is concerned, Zhao
(2010) did not fnd any stable long-term equilibrium relationship between the real
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effective exchange rate and stock prices. He concluded that past innovation in a stock
market affects future volatility in an exchange market and vice versa. Conversely, Cao
et al. (2012) discovered that the cross-correlation between the Chinese exchange market
and its stock market varies with time and is sensitive to the RMB exchange rate regime.
Meanwhile, the fndings of Chkili et al. (2012), suggesting that there is a signifcant
bilateral relationship between the stock and exchange markets for France and Germany,
are consistent with those of Pan et al. (2007). In another study, Chkili and Nguyen (2014)
noticed that the stock market has more infuence on exchange rates in both calm and
turbulent periods for BRICS countries.
This literature reviewillustrates that a lot of research has been carried out exploring
the relationship between exchange rates and stock markets and fnding the equilibrium
exchange rate for the RMB, but comparatively little has been done to assess the
relationship between country risk and the exchange rate of the RMB. Accordingly, the
present study explores the impact of country risk and stock prices on the exchange rate
of the RMB to bridge this gap.
3. Extended open macroeconomic model
Following Hsing (2008), this study uses an extended open macroeconomic model to
ascertain the relationships between country risk, stock prices and the exchange rate of
the RMB. According to this model, aggregate spending is a function of real output, real
interest rate, government spending, government revenue, real exchange rate, stock
prices and world output. Real money demanded is a function of nominal interest rate
stock prices and real output. Infation rate is infuenced by expected infation rate and
the difference between actual and potential output. Hence, the open macroeconomic
model for China is presented as:
Y ? E(Y, R ? X ? ?
e
, G, T, ?, S, Y
*
)
M ? L
(
R ? X, Y, S
)
? ? ?
e
? A(Y ? Y
n
)
where Ystands for real GDP; E, aggregate expenditure; (R?X??
e
), real interest rate;
R, world interest rate; X, country risk; ?
e
, expected infation; G, government spending;
T, government tax revenue; ? , real exchange rate; S, stock index; Y*, world output; M,
money supply; L, real demand for money; ? , infation rate; and Y
N
, potential output.
Let:
E
Y
? 0, E
R?X??e
? 0, E
G
? 0, E
T
? 0, E
?
? 0, E
S
? 0, E
Y*
? 0, L
R?X
? 0,
L
Y
? 0, L
S
? or ? 0, ?
Y
? A?0
Solving for the three unknowns – Y, ? and ?– by applying the implicit function theorem,
the equilibrium exchange rate of RMB can be expressed as:
? ? ?(M, G, T, S, X, R, ?
e
, Y
*
;?, A, Y
N
)
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According to the above model, a higher stock price would be expected to increase the
exchange rate if the demand for money has a positive relationship with the stock price.
Mathematically, this is represented as:
??
?S
?
L
S
(1 ? E
Y
) ? L
Y
E
S
?
J
?
? 0 If L
S
? 0
On the other hand, a higher country risk would be expected to result in a lower ? .
Mathematically, this is expressed as:
??
?X
?
L
X
(1 ? E
Y
) ? L
Y
E
X
?
J
?
? 0
where:
?
J
?
? ?L
Y
E
?
? 0
4. Methodology
4.1 Sample
To ascertain the relationship between country risk, stock market index and the
exchange rate of the RMB, data were been obtained froma number of sources, including
the International Monetary Fund’s International Financial Statistics and the Economist
Intelligence Unit’s Country data. The study period was fromJanuary 2000 to December
2013, representing 168 observations in total. Annual data regarding country risk and
exchange rate were converted into monthly data using linear interpolation. To calculate
the monthly values, the yearly value was deemed the year-end value.
4.2 Variables
Our sample included data concerning four different variables: the nominal exchange
rate of the RMB, the country risk of China, the Shanghai Stock Exchange (SSE)
composite index and a dummy variable. The exchange rate of the RMB is a direct quote
(i.e. the value of the RMB per US dollar). Thus, an increase in the value means a
depreciation of the RMB and vice versa.
The average interest rate on newexternal debt commitments was used as a proxy for
the country risk of China. Higher interest rates mean a high risk of default and vice
versa. The interest rate on external debt represents the average interest rate on all new
public and publically guaranteed loans contracted during the year. To obtain the
average, the interest rates for all public and publically guaranteed loans were weighted
by the amounts of the loans. The causality of the relationship between the exchange rate
of the RMB and country risk is ambiguous; Bordo et al. (2009) identifed that changes in
the exchange rate caused fuctuations in country risk, yet Hsing (2008) found the
opposite to be the case.
The Chinese stock market was represented by the SSE’s “A” share price index. All
monthly values were end-of-the-period values. Note that the relationship between the stock
market and exchange rates is ambiguous, too, with studies publishing dissimilar fndings.
Adummy variable (“D05”) was used to capture the effect of regime change. Its value
was designated as “1” from July 2005 onwards, and “0” prior to that date. In 2005, the
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Chinese authorities decided to value the exchange rate of the RMB in reference to a
basket of currencies rather than against the US dollar alone.
5. Descriptive statistics and correlation matrix
Tables I and II present the descriptive statistics and the correlation matrix of the study’s
variables. The average value of the RMB per US dollar was 6.196 over the study period,
with a standard deviation of 78 per cent. The series was negatively skewed and had a
platykurtic distribution. The average interest rate on external debt commitments was
4.135 per cent. This series was also negatively skewed, and the distribution was near
normal. The average value of the SSEAshare price index was 2,319.35, with a very high
standard deviation of 945.223. This series was positively skewed and leptokurtic, which
means that it included extreme values as well.
The correlation matrix presented in Table II suggests that there is positive
correlation between the country risk of China and the exchange rate of the RMB. This
means that, when the RMB depreciates, the value of the country risk increases and vice
versa. The correlation between the stock market and the exchange rate is shown to be
negative, which means that, when Chinese stock market performs well, the value of the
RMB appreciates and vice versa. Table II illustrates that the exchange rate of the RMB
appreciated after the exchange rate regime change in 2005. The correlation between
regime change and country risk is negative, while it is positive for the stock market. This
means that the country risk of China decreased after 2005, and the performance of the
stock market improved afterwards.
Table I.
Descriptive statistics
N Mean Minimum Maximum SD Skewness Kurtosis
ER 168 7.545 6.196 8.279 0.784 ?0.439 1.494
CR 168 4.135 1.538 6.222 1.194 ?0.174 2.235
SMI 168 2,319.355 1,113.290 6,251.530 945.223 1.613 6.289
D05 168 0.607 0.000 1.000 0.490 ?0.439 1.193
Notes: Table I reports the summary statistics of the nominal exchange rate of the RMB per US dollar
(ER); the average interest rate on new external debt commitments, used as a proxy for the country risk
(CR); SSE A share price index (SMI); and a dummy variable representing the shift in the exchange rate
regime in 2005 (D05)
Table II.
Correlation matrix
ER CR SMI D05
ER 1
CR 0.751*** (0.000) 1
SMI ?0.385*** (0.000) ?0.016 (0.842) 1
D05 ?0.751*** (0.000) ?0.470*** (0.000) 0.527*** (0.000) 1
Notes: Table II reports the pair-wise correlation matrix of the series used in this study’s analysis;
parentheses denote p values, and *, ** and ***represent levels of statistical signifcance at 10, 5 and
1% levels, respectively; see Table I for defnitions of the ER, CR, SMI and D05 variables
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6. Econometric model
To determine the relationships between country risk, the stock market and the exchange
rate of the RMB, we checked all of the series for stationarity by using an augmented
Dickey–Fuller test with 13 lags. We calculated lag length based on Schwert’s rule of
thumb:
P
max
?
?
12 ·
(
T
100
)
1
4
?
where T is the number of observations. We were unable to reject the null hypothesis of
the unit root for all of the series. To ascertain the level of integration, we applied the
Dickey–Fuller test on the frst and second differences of the series and found that the
stock market index was integrated at the frst order, and the other two series were
integrated at the second order. Table III presents the results of the augmented Dickey–
Fuller test.
As the exchange rate and country risk were perceived to be integrated at the same
order, a Johansen test for cointegration was used to identify the cointegration between
them. This test revealed that there is no cointegration between the exchange rate and
country risk of China.
Therefore, as the three series were shown not to be cointegrated, a vector
autoregressive (VAR) model was utilized to explore the relationships between them. The
following set of equations represents the VAR model:
X
t
? ?
10
? ?
11
X
t?2
? ?
12
Y
t?2
? ?
13
Z
t?2
? ?
14
D
t?2
? ?
12
Y
t
? ?
20
? ?
21
X
t?2
? ?
22
Y
t?2
? ?
23
Z
t?2
? ?
24
D
t?2
? ?
22
Z
t
? ?
30
? ?
31
X
t?2
? ?
32
Y
t?2
? ?
33
Z
t?2
? ?
34
D
t?2
? ?
32
D
t
? ?
40
? ?
41
X
t?2
? ?
42
Y
t?2
? ?
43
Z
t?2
? ?
44
D
t?2
? ?
42
where Xstands for exchange rate, Yfor country risk, Z for stock market index and Dfor
the dummy variable. The subscripted t represents time and t-2 represents the second
lag. ? represents the intercept for each equation and ?,?,? and ? represent the slope
coeffcients of exchange rate, country risk, stock prices and the dummy variable,
respectively. ? represents the error term. The lag length of two was selected based on
factor price equalization, the Akaike information criterion, the Hannan–Quinn
information criterion and Schwarz’s Bayesian information criterion.
Table III.
Augmented Dickey–
Fuller test for unit
roots
Variable
Test in level Test in frst difference Test in second difference
No. of trend Trend No. of trend Trend No. of trend Trend
ER ?0.303 ?2.467 ?1.936 ?1.921 ?3.702* ?3.737*
CR ?1.733 ?3.195 ?2.68 ?2.661 ?4.292* ?4.273*
SMI ?1.753 ?1.884 ?5.441* ?5.441*
Notes: Based on Schwert’s rule of thumb, the lag length for all the series is 13; *denotes stationarity;
See Table I for defnitions of the ER, CR and SMI variables
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7. Empirical fndings
Table IV presents the relationships found between the exchange rate, country risk and
the stock market for the whole sample, while Tables Vand VI details these relationships
before and after the regime change of 2005, respectively. All coeffcients represent the
relationships between the second lag of the independent variable and the dependent
variable. According to these results, country risk is not a signifcant determinant of the
exchange rate of the RMB, but the stock market is. The relationship between the stock
Table IV.
Relationship between
the exchange rate,
country risk and the
stock market index
for overall sample
Dependent variables
ER CR SMI D05
ER 0.989*** (232.530) 0.104*** (3.030) 48.613 (0.700) 0.016 (0.690)
CR ?0.002 (?0.910) 0.965*** (55.220) 55.743 (1.570) ?0.013 (?1.070)
SMI ?1.1E-05*** (?5.380) ?3.3E-05** (?1.960) 0.868*** (25.410) ?5.82E-06 (?0.510)
D05 ?0.043*** (?8.370) 0.131*** (3.160) 293.780*** (3.490) 0.980*** (35.040)
CONS. 0.122*** (4.090) ?0.680*** (?2.840) ?463.682 (?0.950) ?0.031 (?0.190)
Notes: Table IVrepresents the relationship between the exchange rate of the RMB, the country risk of
China, the SSE A share stock index and a dummy variable representing the exchange rate regime
change in 2005; parentheses denote z values, and *, **and ***represent statistical signifcance at 10,
5 and 1% levels, respectively; see Table I for defnitions of the ER, CR, SMI and D05 variables
Table V.
Relationship between
the exchange rate,
country risk and the
stock market index
before July 2005
Dependent variables
ER CR SMI
ER 1.585*** (23.490) ?11.964*** (?2.660) 8,697.958** (2.330)
CR 0.00005 (0.110) 0.954*** (35.050) 54.150** (2.390)
SMI 1.3E-06 (0.800) 0.000235** (2.170) 0.732688*** (8.120)
CONS. ?4.842*** (?8.690) 98.785*** (2.660) ?71,808.9** (?2.320)
Notes: Table V reports the relationship between the exchange rate of the RMB, the country risk of
China and the stock market index before the exchange rate regime change in 2005; parentheses denote
z values, and *, **and ***represent statistical signifcance at 10, 5 and 1% levels, respectively; see
Table I for defnitions of the ER, CR and SMI variables
Table VI.
Relationship between
the exchange rate,
country risk and the
stock market index
after July 2005
Dependent variables
ER CR SMI
ER 1.0171*** (90.57) 0.3588*** (4.83) ?87.0766 (?0.49)
CR ?0.0289*** (?3.98) 0.7996*** (16.65) 198.2458* (1.72)
SMI ?0.00001*** (?3.61) ?0.00002 (?0.79) 0.7533*** (12.60)
CONS. ?0.0378 (?0.61) ?1.8004*** (?4.41) 586.8742 (0.60)
Notes: Table VI reports the relationship between the exchange rate of the RMB, the country risk of
China and the stock market index after the exchange rate regime change in 2005; parentheses denote z
values, and *, ** and ***represent statistical signifcance at 10, 5 and 1% levels, respectively; see
Table I for defnitions of the ER, CR and SMI variables
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market and the exchange rate is negative, which means that, when the Chinese stock
market performs well, the value of the RMB appreciates. The coeffcient of the dummy
variable illustrates that the value of the RMB appreciated after the regime change.
Interestingly, the results of the second equation reveal that exchange rate is a highly
signifcant determinant of country risk in the case of China, and a depreciation of the
exchange rate results in a higher country risk. This fnding is in accordance with that of
Bordo et al. (2009). The last column of Table IV illustrates that none of the three
variables explain the variation following regime change.
The results of a Granger-causality Wald test reveal that, in the case of China, country
risk does not Granger-cause the exchange rate, but the stock market and regime changes
do. On the other hand, the exchange rate Granger-causes country risk. This fnding is in
accordance with that of Tsagkanos and Siriopoulos (2013), who discovered that, in the
case of the USA, the exchange rate Granger-causes country risk in the short term. The
country risk of China is also caused by the stock market and regime shift. Interestingly,
neither the exchange rate nor country risk Granger-causes stock prices, but the stock
market Granger-causes both the exchange rate and country risk. Furthermore, a shift in
the exchange rate regime Granger-causes stock market variations. This study’s fndings
regarding regime change are in accordance with those of Cao et al. (2012).
To get an understanding of the effect of regime change on the relationship between
country risk, stock prices and the exchange rate, the study’s sample was divided into
two parts: pre- and post-2005. In July 2005, the authorities in China decided to calculate
the value of the RMBwith reference to a basket of currencies rather than simply against
the US dollar. The present study’s results presented in Table V reveal that neither
country risk nor the stock index used were signifcant determinants of variation in the
nominal exchange rate of the RMB prior to the exchange rate regime change in 2005.
However, the exchange rate and the stock market index used were signifcant
determinants of country risk in the previous regime. Surprisingly, depreciation of the
RMB was associated with lower country risk, and better performance of the stock
market was associated with higher country risk for China. On the other hand,
depreciation of the exchange rate was associated with better performance of stock
market, and higher country risk was also associated with a better performance of the
stock market. The results of the Granger-causality Wald test suggest that neither
country risk nor the stock market used Granger-caused the exchange rate of the RMBin
the previous regime. However, the exchange rate used did Granger-cause country risk.
Thus, the causality was fromexchange rate to country risk. The stock market index was
Granger-caused by the exchange rate as well as country risk.
Table VI represents the relationship between the exchange rate, country risk and
stock market in the study period after the regime change in 2005. All of the results for
this period are based on three lags, as suggested by the Akaike information criterion.
Table VI shows that, in this post-regime change period, both country risk and the stock
market are signifcant determinants of the exchange rate of the RMB. An increase in
country risk is associated with an appreciation of the exchange rate, and a better
performance of the stock market results in an appreciation of the exchange rate as well.
In this period, the exchange rate is also a signifcant determinant of country risk, which
means that a depreciation of the exchange rate results in a higher country risk.
Interestingly, in this period, neither country risk nor the exchange rate determines a
variation in stock prices. A Granger-causality Wald test reveals that both country risk
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and stock index Granger-cause the exchange rate. On the other hand, the exchange rate
also causes country risk, but the stock market index does not. Furthermore, neither
exchange rate nor country risk Granger-cause stock market movements.
So, according to these results, the relationship between country risk, the exchange
rate and the stock market index changed after the regime change. Before 2005, country
risk was not a signifcant determinant of the exchange rate, and this was also true the
other way around, with the relationship between country risk and the stock market
being bidirectional. Exchange rate was a signifcant determinant of both country risk
and the stock market in the previous regime, whereas the relationship between country
risk and the exchange rate is bidirectional in the current regime. Variation in the stock
market explains the variation in the exchange rate, but neither country risk nor the
exchange rate explains variation in the stock market index.
8. Conclusion
This study’s results regarding the short-term relationship between country risk, stock
prices and the exchange rate reveals that, in the case of China, exchange rate
Granger-causes country risk, but not the other way around. Similarly, the stock market
index Granger-causes exchange rate, but the reverse is not true. The relationship
between country risk and the stock market index is also unidirectional (i.e. from stock
market to country risk). Thus, the variation in country risk is explained by both the
exchange rate and stock prices, but the variation in the exchange rate is only explained
by the stock market index. Variation in the stock market index is explained by neither
the exchange rate nor country risk.
These fndings suggest that a better performance of the stock market results into the
appreciation of the RMB. This may be because of the portfolio investment fowing into
the stock markets of the country, as a result of which demand for the RMBincreases and,
in turn, the RMB appreciates. Furthermore, a better performance of the stock market is
shown to be linked with lower country risk, which increases when the RMBdepreciates.
This fnding is in accordance with that of Bordo et al. (2009), who found that exchange
rate depreciation results in a higher sovereign risk if the country in question is exposed
to foreign country debt.
Based on this study’s results, it is proposed that the authorities in China should
revalue the exchange rate of the RMB. The degree of revaluation should be around 15
per cent, as suggested by Zhang and Pan (2004) and Goldstein and Lardy (2006). Such a
revaluation will result in lower country risk, which in turn will bring about lower
interest on new external debt commitments for the government. The authorities could
achieve this goal of revaluation by improving the stock markets and attracting more
portfolio investment, because, according to the study’s results, if the stock market
performs better, the value of the RMB appreciates. Secondly, better stock markets will
boost investment, which will result in higher investment and lower unemployment. This
approach would help the authorities to maintain the new normal model of growth.
References
Bordo, M.D., Meissner, C.M. and Weidenmier, M.D. (2009), “Identifying the effect of an exchange
rate depreciation on country risk: evidence from a natural experiment”, Journal of
International Money and Finance, Vol. 28 No. 6, pp. 1022-1044.
375
Exchange rate
of the
renminbi
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
1
:
5
3
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Cao, C., Xu, L. and Cao, J. (2012), “Multifractal detrended cross-correlations between the Chinese
exchange market and stock market”, Physica A, Vol. 391 No. 20, pp. 4855-4866.
Chkili, W., Aloui, C. and Nguyen, D.K. (2012), “Asymmetric effects and long memory in dynamic
volatility relationships between stock returns and exchange rates”, Journal of International
Financial Markets, Institutions & Money, Vol. 22 No. 4, pp. 738-757.
Chkili, W. and Nguyen, D.K. (2014), “Exchange rate movements and stock market returns in a
regime-switching environment: evidence for BRICS countries”, Research in International
Business and Finance, Vol. 31, pp. 46-56.
Chou, W.L. and Shih, Y.C. (1998), “The equilibriumexchange rate of Chinese renminbi”, Journal of
Comparative Economics, Vol. 26 No. 1, pp. 165-174.
Goldstein, M. and Lardy, N. (2006), “China’s exchange rate policy dilemma”, The American
Economic Review, Vol. 96 No. 2, pp. 422-426.
Heinrichs, M. and Stanoeva, I. (2012), “Country risk and sovereign risk: building clearer borders”,
Euromoney Risk Management Handbook, Euromoney Trading, London, pp. 15-24.
Hsing, Y. (2008), “The impacts of the stock price and country risk on the exchange rate in
Singapore”, International Journal of Development Issues, Vol. 7 No. 1, pp. 56-61.
Huang, H. and Wang, S. (2004), “Exchange rate regimes: China’s experience and choices”, China
Economic Review, Vol. 15 No. 3, pp. 336-342.
Kuttner, K.N. and Mosser, P. (2002), “The monetary transmission mechanism: some answers and
further questions”, Federal Reserve Bank of NewYork Economic Policy Review, Vol. 8 No. 1,
pp. 15-26.
Nieh, C.C. and Lee, C.F. (2001), “Dynamic relationship between stock prices and exchange rates for
G-7 countries”, The Quarterly Review of Economics and Finance, Vol. 41 No. 4, pp. 477-490.
Pan, M.S., Fok, R.C.W. and Liu, Y.A. (2007), “Dynamic linkages between exchange rates and stock
prices: evidence fromEast Asian markets”, International Reviewof Economics and Finance,
Vol. 16 No. 4, pp. 503-520.
Tsagkanos, A. and Siriopoulos, C. (2013), “Along-run relationship between stock price index and
exchange rate: a structural nonparametric cointegrating regression approach”, Journal of
International Financial Markets, Institutions & Money, Vol. 25 No. 1, pp. 106-118.
Wang, T. (2005), “Sources of real exchange rate fuctuations in China”, Journal of Comparative
Economics, Vol. 33 No. 4, pp. 753-771.
Zhang, F. and Pan, Z. (2004), “Determination of China’s long-run nominal exchange rate and
offcial intervention”, China Economic Review, Vol. 15 No. 3, pp. 360-365.
Zhao, H. (2010), “Dynamic relationship between exchange rate and stock price: evidence from
China”, Research in International Business and Finance, Vol. 24 No. 2, pp. 103-112.
Further reading
Mankiw, N.G. (2007), Macroeconomics, 6th ed., Worth, New York, NY.
Corresponding author
Gang Sun can be contacted at: [email protected]
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