Description
Financial modeling is the task of building an abstract representation (a model) of a real world financial situation.[1] This is a mathematical model designed to represent (a simplified version of) the performance of a financial asset or portfolio of a business, project, or any other investment.
SUMMARY REPORT TO THE SECTION 41 ROBE MARINA COMMITTEE DISTRICT COUNCIL OF ROBE MARINA FINANCIAL MODELLING PROJECT
Dr Geoff Wells, MIMC Management Consultant PO Box 167 Robe SA 5276 April 2010
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SUMMARY REPORT TO THE SECTION 41 ROBE MARINA COMMITTEE DISTRICT COUNCIL OF ROBE MARINA FINANCIAL MODELLING PROJECT 1. Background In late September 2009 the Council engaged Dr Geoff Wells to assist it in the development of a financial modelling tool, which could be used in the context of developing plans for the Robe Marina. The brief was to assist Council administration by working with Bill Hender , Council CEO, and Vanessa Macdonald, Council Accountant, in developing this tool. Important elements of the brief were: It was intended that the tool would then be used by the Section 41 Committee and the Council to test the financial implications of the different strategic scenarios which might be available to take the Marina forward. ? It was agreed that it was not Dr Wells’s role to make policy recommendations, but to help develop the financial modelling tool and to support its use in testing business plan scenarios developed by the Section 41 Committee and by Council. ? Although previous modelling, including the original modelling by the Marina Corporation and subsequent modelling in reports, was expected to be reviewed, it was not part of this brief to express an opinion on the methodologies of these models or their outcomes. All input data for the modelling in the project was to be developed and tested under current conditions. ? The brief did not include consideration of potential entity and management structures for the Marina going forward. ? Dr Wells was further charged with overseeing a process by which key inputs into the modelling tool would be elicited from all sections of the community, in an open and transparent manner. 2. Procedure The following steps were laid out at the beginning of the process, in consultation with the Section 41 Committee and the Administrations, and have been carefully and throughly implemented: 1) A stakeholder review was undertaken. This comprised an open invitation to elected members, Section 41 Committee members, commercial berthholders, recreational berthholders, ratepayers, and the community in general to contact Dr Wells to make their views and opinions known. Over the succeeding months more than 50 individuals, representing all stakeholder groups, took up that offer. Many concerns and creative ideas were expressed, and where possible were applied to the modelling task. 2) A full review of relevant documentation was undertaken. This included the Jones report, the Venn report, documentation from the former Robe Marina Corporation (including financial ?
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projections), other technical reports in the hands of Council, State and agency reports, and current audited financial statements of Council and the Marina project. 3) A data gathering exercise was undertaken, focused mainly on the key financial data that was either missing or unclear or in dispute, that were required inputs into the financial model. This data was retrieved by revisiting quotes with providers (for example, for sheet piling repair and replacement), or seeking expert opinion, (for example, on berth dredging costs), or reviewing comparable numbers (for example, on berth pricing). Some of this information was available from stakeholders, some from external providers. The project brief required that every relevant number had to be revisited under current conditions, whether or not it had been proposed previously, because substantial time had elapsed since those exercises, and because professional standards of due diligence required it. 4) Financial model development was then undertaken. Key decisions relating to the model’s parameters were made (time horizon, nominal or real approaches, inflation rates, interest rates, cost of capital, terminal value, as detailed below). Spreadsheet development followed, in Projected Statements of Financial Performance (Profit and Loss), Projected Statements of Financial Position (Balance Sheet) and Projected Statements of Cash Flow. Free Cash Flow (FCF) estimates were generated across the time horizon, and the Net Present Value (NPV) of FCF calculated. In consultation with management Sensitivity Analysis was carried out on key variables, and the financial implications of a number of management scenarios were explored. This approach to the financial modelling has strong support in the professional literature, where it is regarded as best practice. In addition, it was checked with external finance professionals and supported by them. 5) Consultation was then undertaken with key stakeholder groups, particular the executive groups of professional and recreational berthholders, and then with the wider berthholder constituencies, including ratepayers. On a number of occasions, the modelling of the project as it developed was presented to these groups and feedback invited. Various proposals of lease lengths, both current and future were presented and discussed. Input from these meetings was then taken back as inputs to the modelling development.
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3. Key data inputs to the model At the outset of the modelling project there were many uncertainties about key data inputs. The process outlined above produced the following results on these inputs:
Item Time horizon—leases Data 99 year leases 50 years leases 40 year leases 30 year leases and combinations for current and new leases. Current pricing. Pricing on future berth sales. Sensitivity analysis on future pricing carried out. Comments The time horizon of the model is determined by the lease options being contemplated. Leases generate liabilities for the lessor throughout the lease period.
Berth pricing
Current prices were benchmarked against other Marinas in South Australia and interstate. They were found to represent excellent value for money against comparisons.
Dredging: berths Dredging: channel Underwater bund
$800,000 every 40 years $200,000 every 5 years $100,000
To secure dredged material in the Marina basin as per proposal to the EPA.
Marina refurbishing Sheet piling replacement
Straddle lift jetty refurbishment Straddle lift replacement Breakwater rebuild Washdown area renovation Car park renovation Financing costs Cost of capital
$3.2m, every 40 years $2.8m, in 22 years, and then in 40 years. $600,000 in 30 years, then in 50 years. $400,000 in 15 years, then at 40 year intervals. $72,000 in 30 years, then in 40 years. $11,000 in 37 years, then in 40 years. $67,000 in 27 years, then at 30 year intervals. 7% 7% selected Sensitivity testing on lower and
Initial quote of 4.8m was renegotiated to 2.8m.
Average long?term trend Current recommendation of State Treasuries and of Federal agencies.
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higher discount rates carried out.
Valuation framework
Real (inflation adjusted) Nominal (in today’s dollars)
Operating costs
Current, projected
Commercial projects would apply a higher rate, socially?oriented projects a lower rate. This rate reflects the role of local government as a provider of social services, and the character of the Marina as a quasi?commercial project. Both frameworks are used in project finance and both were modelled. Best practice is to use Real valuation, particularly over longer project horizons, and the model presented is in Real terms. General, Selling and Administration costs were estimated from current levels, and included provision for marketing around lease resales.
4. Modelling methodology Net Present Value (NPV) is the standard measure used for evaluating the financial viability of capital projects. It aggregates the annual financial results of the project and allows for the time value of money, by which amounts recorded in the future are discounted to calculate their present value. The annual net cash flows generated by the project are aggregated using the standard formula to calculate the project’s NPV. A positive NPV indicates that surplus value is being created by the project; a negative NPV that value is being destroyed by the project. While not the only determinant of a go/no go decision, the NPV result is typically held to be critical to the evaluation of potential projects. It is a required input to any capital works or business project proposed by local government. The cash flows aggregated in this model are Free Cash Flows (FCF). FCF is calculated by adjusting annual net operating profit to cash, and then deducting amounts for the requirements of the business. Charges are made for the change in non?cash working capital and investment in fixed assets. This ensures that the liquidity and investment requirements of the business are provided for. The surplus is termed Free Cash, and is the basis of the additional economic value being generated by the project. While project modelling is also carried out using net annual cash movements, FCF is regarded in professional theory and practice as best practice1. It is a conservative approach with respect to risk. This approach was supported by external professional advisors.
Martin, J & Petty, J 2000, Value Based Management, Harvard Business School Press, Boston, MA.; Damodaran, A 2006, Damodaran on valuation: security analysis for investment and corporate finance, 2nd edn., John Wiley & Sons, New Jersey.
1
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FCF analysis requires data to be drawn in from all three annual financial statements (Statements of Financial Performance, Financial Position and Cash Flows). The financial modelling thus proceeds by developing these statements for each year of the project. Capital budgeting is driven by an annual Asset Register. Linked spreadsheets ensure that the Statements are reconciled under GAAP principles. The output of the model is the stream of annual FCFs, which is then aggregated through the NPV calculation. Attention can then be given to the key factors which drive the valuation. In this model those factors were: ? ? ? ? ? Discount rate Income Expenses Capital investment Interest rates
Sensitivity analysis involves exploring the ranges of values that these factors can take, and the financial outcomes of varying the factors in this way. Each business scenario investigated thus has its own set of spreadsheets, generating different FCF and NPV results. These results represent the financial value that would be generated by the project under each scenario. After consulting with external financial modelling experts, as an external review, two additional modifications to this approach were made: ? Under accounting rules lease income is amortised across the lease period, to recognise the ongoing liability under the terms of the lease, which is then progressively paid down. The external reviewer noted that, although strictly correct from an accounting point of view, discounting amortisations over a long period, as the NPV calculation requires, results in a probable underestimate of NPV. This advice was accepted by the modelling team. Accordingly, recommended adjustments to the outcomes were made which had the effect of recognising berth sales in the period in which they occurred. This was held to give a more accurate estimate of the economic outcomes of the project, reflected in the increased NPV values. As noted above, under the standard formula for Free Cash Flow, a charge is made for the change in non?cash working capital, to ensure adequate liquidity. The external reviewer noted that in this case there is no such change, because no accruals are being carried, and that therefore this line item can be eliminated from the Free Cash Calculation. This advice was accepted by the modelling team. Accordingly this adjustment was made.
?
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5. Financial modelling results General assumptions All financial models stand on input assumptions. Changes in these assumptions change the outcomes of the model. In building this model, the following input assumptions were used (notes here refer to the spreadsheet model):
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Income will increase by 3% CPI factor every year. Interest Income will be 5% of previous year’s closing bank account balance. No Grant Income is anticipated. No LGFA bonus has been factored in. Marina Berth Income Premium is the amortisation of the berth payment over the length of the lease (Premium Amortisation Sheet).. Marina Berth Income : Lease Income has been rolled into Administration Fees (Berth Revenue). Marina Berth Income : Short Term Lease Income has been rolled into Administration Fees (Berth Revenue). Administration Fees – refer berth revenue worksheet. No Other Revenue is anticipated. General Rates is included as income. Straddle Hire Fees expected to increase by 10% in 2012/13 with sale of remaining commercial berths and then expected to remain with CPI increase. Mooring Fees has been rolled into Administration Fees (Berth Revenue) – is expected to be 50% utilisation (Berth Revenue) Hardstand Storage expected to increase with CPI. Boat Ramp has been excluded as boat ramp revenue is to be spent on the boat ramp. Fees for Prep Underlease is a one off fee for the preparation of the lease; these have not been included in future years as is offset by legal fees. Separate Rate of $300 is excluded from calculations. Expenses will increase by 3% CPI Factor every year. Advertising will be 10K in first year and 5K for the following 3 years around berth sales every 30 years. Interest Expense expected to be on average 7% of previous years loan balance.
20 No Entry for future losses has been factored in.
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21 22 23 24 25 26 27 27 28 30 31 32 No asset sales are anticipated No Berth refunds are anticipated Marina Development (Pontoons) Replaced every 40 years: 2047, 2087; $3.2m Breakwater Replaced every 40 years: 2047, 2087; $72,000 Washdown Area Replaced every 40 years: 2047, 2087; $11,000 Carpark to be replaced every 30 years: 2037, 2067, 2097; $67,000 Dredging of Channel to be done every 5 years commencing 2010/11, $200,000 Straddle Lift Jetty 50 year life with 30 years remaining life; replacement 2039, 2089; $600,000 Straddle Lift $100K to be spent in 09/10; replacement 2025, 2065, 2105; $400,000 Construction of bund to hold dredge material is expected to last 99 years; $10,000 Dredging of berths $800,000 every 40 years Sheet Piling: replacement $2.8m in 2032, 2072
Importantly, the above assumptions include provisions for maintaining the current leases in their present form, and selling new leases as 30?year leases. Berth pricing assumptions Projections of future revenue streams are critical to the outcomes of the model. The following assumptions with respect to berth pricing were used in this model:
COMMERCIAL KARATTA WATERHOUSE BUTLER 60,000 70,000 40,000 25,000 25,000 90,000 60,000 50,000 99 Year Leases 59,000 72,000 30 Year Leases 59,000 21 Year Leases
As noted, these price levels were set taking into account pricing at other state marinas, and feedback from the current berthholder groups. 8 | P a g e
Result Under these assumptions the model generated the following a positive Net Present Value for the project of $1,225, 720. 6. Uncertainties and risk coverage As noted, the financial model must be built to encompass the length of leases, which generate liabilities throughout the lease period, in this case 99 years for the longest leases. This time horizon is unusually long for a financial model, and presents a challenge to model reliability. In particular, risks and uncertainties associated with the project are material to any decision?making of which this model is a part. The key variables governing values in this model—revenues, expenses, capital investment, interest rates, cost of capital—are clearly subject to substantial uncertainty over the long time?horizons. Standard sensitivity analysis has been carried out with respect to these variables. Expenses and capital investment were assumed likely to move over narrower ranges. It was also assumed that interest rates ranges would kept in check by current central banking policies. Therefore revenues and discount rates were the focus of the sensitivity analysis. It should be emphasised that full actuarial methods would be required to better capture uncertainties and risks. However, the modelling presented here has been built on the principle that reasonable estimates of these variables, backed with data and sound methodology, and documenting potential ranges of values in a systematic way, meets the requirements for project modelling under the Local Government Act. Some comments on key financial risks now follow: ? Berth income: The financial results of the model are quite sensitive to variations in income. Sensitivity analysis indicates that, using the 7% discount rate, approximately 80% of new berths would need to be sold when they are offered, in order to maintain a positive NPV for the project. At sales levels less than this the NPV for the project becomes negative. Timing of income may also impact the financial outcome. Discount rates: The cost of capital increases with increasing interest rates, and the discount rate with it. The discount rate of 7% used in this model is at present standard for most state and federal government treasury modelling. NPV decreases with increases in the discount rate, hence interest rate rises should be monitored carefully for their effect on the projected results. On the other side of the equation, an external finance advisor to the project noted that a lower discount rate, set at the long?term bond rate, could also be justified over such an extended time horizon—using the current 10?year bond yield of 5.8% the model would generate an increase in projected NPV over the current outcome. Thus the 7% discount rate 9 | P a g e
?
recommended represents a conservative approach to the modelling, and may be seen as providing a safety margin, based on this approach. ? Grant income: Financial flexibility for the Council was built into the modelling by not including a revenue line item for government grants. It is likely that grants will be available and may be secured, but in order to present a conservative position the decision was made not to include them. Climate change impacts: Based on recent reports2, climate change impacts on the project are possible over such a long period of time, and adaptation measures associated with them may have a bearing on the financial viability of the project. For example, it is possible that climate change over the period may produce a significant increase in storm surges, with resulting damage to infrastructure, or a requirement to upgrade it. In this model it is assumed that targeted government funding for such purposes is likely to be available, and will be pursued by Council. These impacts, on both cost and revenue sides, have therefore not been included in this model.
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2
Commonwealth of Australia 2009, Managing our coastal zone in a changing climate, House of Representatives Standing Committee on Climate Change, Water, Environment and the Arts, Canberra.
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Summary and conclusions The brief for this project was for the creation of a modelling tool which the Section 41 committee and the Council could use to test the financial implications of forward strategies for the Marina. That modelling tool is now in place. What is reported in this Summary Report are some of the outcomes of using the tool to predict financial outcomes under different financial scenarios. This does not in any way exhaust the possibilities: there are certainly other scenarios that could be proposed and tested under the model by the Section 41 Committee and the Council. A central part of the project was to develop robust current numbers for key inputs to the model. The project has delivered such numbers. However, it should be noted that these numbers will continue to change, and will need to be revisited over time. Under the assumptions listed here, the model indicates a positive NPV that is reasonably robust under key risk sensitivities. However, it has also been noted that relatively small shifts in some of the key drivers, particularly revenues and discount rate, can deliver a negative NPV. Any decision? making which incorporates these model outcomes should therefore pay close attention to the risk probabilities associated with these measures. A parallel outcome of the project has been the successful implementation of the consultation process with all major stakeholders.
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Disclaimer
Dr Geoff Wells has prepared this report with the usual care and thoroughness of the management consulting profession. It was based on data provided or approved by the client and on generally accepted practices and standards at the time it was prepared. No other warranty, expressed or implied, is made as to the accuracy or professional advice contained herein. Dr Wells has made no independent valuation beyond the scope of work contained herein, assumes no responsibility for omissions or the accuracy of the information provided, and accepts no liability for conclusions drawn or actions taken based on the information contained in this report.
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doc_771558681.pdf
Financial modeling is the task of building an abstract representation (a model) of a real world financial situation.[1] This is a mathematical model designed to represent (a simplified version of) the performance of a financial asset or portfolio of a business, project, or any other investment.
SUMMARY REPORT TO THE SECTION 41 ROBE MARINA COMMITTEE DISTRICT COUNCIL OF ROBE MARINA FINANCIAL MODELLING PROJECT
Dr Geoff Wells, MIMC Management Consultant PO Box 167 Robe SA 5276 April 2010
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SUMMARY REPORT TO THE SECTION 41 ROBE MARINA COMMITTEE DISTRICT COUNCIL OF ROBE MARINA FINANCIAL MODELLING PROJECT 1. Background In late September 2009 the Council engaged Dr Geoff Wells to assist it in the development of a financial modelling tool, which could be used in the context of developing plans for the Robe Marina. The brief was to assist Council administration by working with Bill Hender , Council CEO, and Vanessa Macdonald, Council Accountant, in developing this tool. Important elements of the brief were: It was intended that the tool would then be used by the Section 41 Committee and the Council to test the financial implications of the different strategic scenarios which might be available to take the Marina forward. ? It was agreed that it was not Dr Wells’s role to make policy recommendations, but to help develop the financial modelling tool and to support its use in testing business plan scenarios developed by the Section 41 Committee and by Council. ? Although previous modelling, including the original modelling by the Marina Corporation and subsequent modelling in reports, was expected to be reviewed, it was not part of this brief to express an opinion on the methodologies of these models or their outcomes. All input data for the modelling in the project was to be developed and tested under current conditions. ? The brief did not include consideration of potential entity and management structures for the Marina going forward. ? Dr Wells was further charged with overseeing a process by which key inputs into the modelling tool would be elicited from all sections of the community, in an open and transparent manner. 2. Procedure The following steps were laid out at the beginning of the process, in consultation with the Section 41 Committee and the Administrations, and have been carefully and throughly implemented: 1) A stakeholder review was undertaken. This comprised an open invitation to elected members, Section 41 Committee members, commercial berthholders, recreational berthholders, ratepayers, and the community in general to contact Dr Wells to make their views and opinions known. Over the succeeding months more than 50 individuals, representing all stakeholder groups, took up that offer. Many concerns and creative ideas were expressed, and where possible were applied to the modelling task. 2) A full review of relevant documentation was undertaken. This included the Jones report, the Venn report, documentation from the former Robe Marina Corporation (including financial ?
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projections), other technical reports in the hands of Council, State and agency reports, and current audited financial statements of Council and the Marina project. 3) A data gathering exercise was undertaken, focused mainly on the key financial data that was either missing or unclear or in dispute, that were required inputs into the financial model. This data was retrieved by revisiting quotes with providers (for example, for sheet piling repair and replacement), or seeking expert opinion, (for example, on berth dredging costs), or reviewing comparable numbers (for example, on berth pricing). Some of this information was available from stakeholders, some from external providers. The project brief required that every relevant number had to be revisited under current conditions, whether or not it had been proposed previously, because substantial time had elapsed since those exercises, and because professional standards of due diligence required it. 4) Financial model development was then undertaken. Key decisions relating to the model’s parameters were made (time horizon, nominal or real approaches, inflation rates, interest rates, cost of capital, terminal value, as detailed below). Spreadsheet development followed, in Projected Statements of Financial Performance (Profit and Loss), Projected Statements of Financial Position (Balance Sheet) and Projected Statements of Cash Flow. Free Cash Flow (FCF) estimates were generated across the time horizon, and the Net Present Value (NPV) of FCF calculated. In consultation with management Sensitivity Analysis was carried out on key variables, and the financial implications of a number of management scenarios were explored. This approach to the financial modelling has strong support in the professional literature, where it is regarded as best practice. In addition, it was checked with external finance professionals and supported by them. 5) Consultation was then undertaken with key stakeholder groups, particular the executive groups of professional and recreational berthholders, and then with the wider berthholder constituencies, including ratepayers. On a number of occasions, the modelling of the project as it developed was presented to these groups and feedback invited. Various proposals of lease lengths, both current and future were presented and discussed. Input from these meetings was then taken back as inputs to the modelling development.
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3. Key data inputs to the model At the outset of the modelling project there were many uncertainties about key data inputs. The process outlined above produced the following results on these inputs:
Item Time horizon—leases Data 99 year leases 50 years leases 40 year leases 30 year leases and combinations for current and new leases. Current pricing. Pricing on future berth sales. Sensitivity analysis on future pricing carried out. Comments The time horizon of the model is determined by the lease options being contemplated. Leases generate liabilities for the lessor throughout the lease period.
Berth pricing
Current prices were benchmarked against other Marinas in South Australia and interstate. They were found to represent excellent value for money against comparisons.
Dredging: berths Dredging: channel Underwater bund
$800,000 every 40 years $200,000 every 5 years $100,000
To secure dredged material in the Marina basin as per proposal to the EPA.
Marina refurbishing Sheet piling replacement
Straddle lift jetty refurbishment Straddle lift replacement Breakwater rebuild Washdown area renovation Car park renovation Financing costs Cost of capital
$3.2m, every 40 years $2.8m, in 22 years, and then in 40 years. $600,000 in 30 years, then in 50 years. $400,000 in 15 years, then at 40 year intervals. $72,000 in 30 years, then in 40 years. $11,000 in 37 years, then in 40 years. $67,000 in 27 years, then at 30 year intervals. 7% 7% selected Sensitivity testing on lower and
Initial quote of 4.8m was renegotiated to 2.8m.
Average long?term trend Current recommendation of State Treasuries and of Federal agencies.
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higher discount rates carried out.
Valuation framework
Real (inflation adjusted) Nominal (in today’s dollars)
Operating costs
Current, projected
Commercial projects would apply a higher rate, socially?oriented projects a lower rate. This rate reflects the role of local government as a provider of social services, and the character of the Marina as a quasi?commercial project. Both frameworks are used in project finance and both were modelled. Best practice is to use Real valuation, particularly over longer project horizons, and the model presented is in Real terms. General, Selling and Administration costs were estimated from current levels, and included provision for marketing around lease resales.
4. Modelling methodology Net Present Value (NPV) is the standard measure used for evaluating the financial viability of capital projects. It aggregates the annual financial results of the project and allows for the time value of money, by which amounts recorded in the future are discounted to calculate their present value. The annual net cash flows generated by the project are aggregated using the standard formula to calculate the project’s NPV. A positive NPV indicates that surplus value is being created by the project; a negative NPV that value is being destroyed by the project. While not the only determinant of a go/no go decision, the NPV result is typically held to be critical to the evaluation of potential projects. It is a required input to any capital works or business project proposed by local government. The cash flows aggregated in this model are Free Cash Flows (FCF). FCF is calculated by adjusting annual net operating profit to cash, and then deducting amounts for the requirements of the business. Charges are made for the change in non?cash working capital and investment in fixed assets. This ensures that the liquidity and investment requirements of the business are provided for. The surplus is termed Free Cash, and is the basis of the additional economic value being generated by the project. While project modelling is also carried out using net annual cash movements, FCF is regarded in professional theory and practice as best practice1. It is a conservative approach with respect to risk. This approach was supported by external professional advisors.
Martin, J & Petty, J 2000, Value Based Management, Harvard Business School Press, Boston, MA.; Damodaran, A 2006, Damodaran on valuation: security analysis for investment and corporate finance, 2nd edn., John Wiley & Sons, New Jersey.
1
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FCF analysis requires data to be drawn in from all three annual financial statements (Statements of Financial Performance, Financial Position and Cash Flows). The financial modelling thus proceeds by developing these statements for each year of the project. Capital budgeting is driven by an annual Asset Register. Linked spreadsheets ensure that the Statements are reconciled under GAAP principles. The output of the model is the stream of annual FCFs, which is then aggregated through the NPV calculation. Attention can then be given to the key factors which drive the valuation. In this model those factors were: ? ? ? ? ? Discount rate Income Expenses Capital investment Interest rates
Sensitivity analysis involves exploring the ranges of values that these factors can take, and the financial outcomes of varying the factors in this way. Each business scenario investigated thus has its own set of spreadsheets, generating different FCF and NPV results. These results represent the financial value that would be generated by the project under each scenario. After consulting with external financial modelling experts, as an external review, two additional modifications to this approach were made: ? Under accounting rules lease income is amortised across the lease period, to recognise the ongoing liability under the terms of the lease, which is then progressively paid down. The external reviewer noted that, although strictly correct from an accounting point of view, discounting amortisations over a long period, as the NPV calculation requires, results in a probable underestimate of NPV. This advice was accepted by the modelling team. Accordingly, recommended adjustments to the outcomes were made which had the effect of recognising berth sales in the period in which they occurred. This was held to give a more accurate estimate of the economic outcomes of the project, reflected in the increased NPV values. As noted above, under the standard formula for Free Cash Flow, a charge is made for the change in non?cash working capital, to ensure adequate liquidity. The external reviewer noted that in this case there is no such change, because no accruals are being carried, and that therefore this line item can be eliminated from the Free Cash Calculation. This advice was accepted by the modelling team. Accordingly this adjustment was made.
?
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5. Financial modelling results General assumptions All financial models stand on input assumptions. Changes in these assumptions change the outcomes of the model. In building this model, the following input assumptions were used (notes here refer to the spreadsheet model):
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Income will increase by 3% CPI factor every year. Interest Income will be 5% of previous year’s closing bank account balance. No Grant Income is anticipated. No LGFA bonus has been factored in. Marina Berth Income Premium is the amortisation of the berth payment over the length of the lease (Premium Amortisation Sheet).. Marina Berth Income : Lease Income has been rolled into Administration Fees (Berth Revenue). Marina Berth Income : Short Term Lease Income has been rolled into Administration Fees (Berth Revenue). Administration Fees – refer berth revenue worksheet. No Other Revenue is anticipated. General Rates is included as income. Straddle Hire Fees expected to increase by 10% in 2012/13 with sale of remaining commercial berths and then expected to remain with CPI increase. Mooring Fees has been rolled into Administration Fees (Berth Revenue) – is expected to be 50% utilisation (Berth Revenue) Hardstand Storage expected to increase with CPI. Boat Ramp has been excluded as boat ramp revenue is to be spent on the boat ramp. Fees for Prep Underlease is a one off fee for the preparation of the lease; these have not been included in future years as is offset by legal fees. Separate Rate of $300 is excluded from calculations. Expenses will increase by 3% CPI Factor every year. Advertising will be 10K in first year and 5K for the following 3 years around berth sales every 30 years. Interest Expense expected to be on average 7% of previous years loan balance.
20 No Entry for future losses has been factored in.
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21 22 23 24 25 26 27 27 28 30 31 32 No asset sales are anticipated No Berth refunds are anticipated Marina Development (Pontoons) Replaced every 40 years: 2047, 2087; $3.2m Breakwater Replaced every 40 years: 2047, 2087; $72,000 Washdown Area Replaced every 40 years: 2047, 2087; $11,000 Carpark to be replaced every 30 years: 2037, 2067, 2097; $67,000 Dredging of Channel to be done every 5 years commencing 2010/11, $200,000 Straddle Lift Jetty 50 year life with 30 years remaining life; replacement 2039, 2089; $600,000 Straddle Lift $100K to be spent in 09/10; replacement 2025, 2065, 2105; $400,000 Construction of bund to hold dredge material is expected to last 99 years; $10,000 Dredging of berths $800,000 every 40 years Sheet Piling: replacement $2.8m in 2032, 2072
Importantly, the above assumptions include provisions for maintaining the current leases in their present form, and selling new leases as 30?year leases. Berth pricing assumptions Projections of future revenue streams are critical to the outcomes of the model. The following assumptions with respect to berth pricing were used in this model:
COMMERCIAL KARATTA WATERHOUSE BUTLER 60,000 70,000 40,000 25,000 25,000 90,000 60,000 50,000 99 Year Leases 59,000 72,000 30 Year Leases 59,000 21 Year Leases
As noted, these price levels were set taking into account pricing at other state marinas, and feedback from the current berthholder groups. 8 | P a g e
Result Under these assumptions the model generated the following a positive Net Present Value for the project of $1,225, 720. 6. Uncertainties and risk coverage As noted, the financial model must be built to encompass the length of leases, which generate liabilities throughout the lease period, in this case 99 years for the longest leases. This time horizon is unusually long for a financial model, and presents a challenge to model reliability. In particular, risks and uncertainties associated with the project are material to any decision?making of which this model is a part. The key variables governing values in this model—revenues, expenses, capital investment, interest rates, cost of capital—are clearly subject to substantial uncertainty over the long time?horizons. Standard sensitivity analysis has been carried out with respect to these variables. Expenses and capital investment were assumed likely to move over narrower ranges. It was also assumed that interest rates ranges would kept in check by current central banking policies. Therefore revenues and discount rates were the focus of the sensitivity analysis. It should be emphasised that full actuarial methods would be required to better capture uncertainties and risks. However, the modelling presented here has been built on the principle that reasonable estimates of these variables, backed with data and sound methodology, and documenting potential ranges of values in a systematic way, meets the requirements for project modelling under the Local Government Act. Some comments on key financial risks now follow: ? Berth income: The financial results of the model are quite sensitive to variations in income. Sensitivity analysis indicates that, using the 7% discount rate, approximately 80% of new berths would need to be sold when they are offered, in order to maintain a positive NPV for the project. At sales levels less than this the NPV for the project becomes negative. Timing of income may also impact the financial outcome. Discount rates: The cost of capital increases with increasing interest rates, and the discount rate with it. The discount rate of 7% used in this model is at present standard for most state and federal government treasury modelling. NPV decreases with increases in the discount rate, hence interest rate rises should be monitored carefully for their effect on the projected results. On the other side of the equation, an external finance advisor to the project noted that a lower discount rate, set at the long?term bond rate, could also be justified over such an extended time horizon—using the current 10?year bond yield of 5.8% the model would generate an increase in projected NPV over the current outcome. Thus the 7% discount rate 9 | P a g e
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recommended represents a conservative approach to the modelling, and may be seen as providing a safety margin, based on this approach. ? Grant income: Financial flexibility for the Council was built into the modelling by not including a revenue line item for government grants. It is likely that grants will be available and may be secured, but in order to present a conservative position the decision was made not to include them. Climate change impacts: Based on recent reports2, climate change impacts on the project are possible over such a long period of time, and adaptation measures associated with them may have a bearing on the financial viability of the project. For example, it is possible that climate change over the period may produce a significant increase in storm surges, with resulting damage to infrastructure, or a requirement to upgrade it. In this model it is assumed that targeted government funding for such purposes is likely to be available, and will be pursued by Council. These impacts, on both cost and revenue sides, have therefore not been included in this model.
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2
Commonwealth of Australia 2009, Managing our coastal zone in a changing climate, House of Representatives Standing Committee on Climate Change, Water, Environment and the Arts, Canberra.
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Summary and conclusions The brief for this project was for the creation of a modelling tool which the Section 41 committee and the Council could use to test the financial implications of forward strategies for the Marina. That modelling tool is now in place. What is reported in this Summary Report are some of the outcomes of using the tool to predict financial outcomes under different financial scenarios. This does not in any way exhaust the possibilities: there are certainly other scenarios that could be proposed and tested under the model by the Section 41 Committee and the Council. A central part of the project was to develop robust current numbers for key inputs to the model. The project has delivered such numbers. However, it should be noted that these numbers will continue to change, and will need to be revisited over time. Under the assumptions listed here, the model indicates a positive NPV that is reasonably robust under key risk sensitivities. However, it has also been noted that relatively small shifts in some of the key drivers, particularly revenues and discount rate, can deliver a negative NPV. Any decision? making which incorporates these model outcomes should therefore pay close attention to the risk probabilities associated with these measures. A parallel outcome of the project has been the successful implementation of the consultation process with all major stakeholders.
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Disclaimer
Dr Geoff Wells has prepared this report with the usual care and thoroughness of the management consulting profession. It was based on data provided or approved by the client and on generally accepted practices and standards at the time it was prepared. No other warranty, expressed or implied, is made as to the accuracy or professional advice contained herein. Dr Wells has made no independent valuation beyond the scope of work contained herein, assumes no responsibility for omissions or the accuracy of the information provided, and accepts no liability for conclusions drawn or actions taken based on the information contained in this report.
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