An intensive 5–day course, covering:
- Basic corporate model with macros and instructions to create comprehensive analysis
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Fully developed financial models with debt structuring, debt sizing, contract pricing and sensitivity analysis
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Time series software that incorporates volatility, mean reversion and other parameters into models
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Monte Carlo simulation software that combines times series analysis with financial modelling
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Software that computes implied volatility and option pricing using the Black Scholes model
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Yield spread models that computes the required yield spreads on project finance debt form time series analysis
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Corporate modelling software that extends project finance models to evaluate valuation of entire corporations
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Forward pricing software that projects prices from marginal cost analysis
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A variety of macro exercises that compute debt capacity, resolve circularity, develop tornado diagrams and construct vintage depreciation
Course summary
The course addresses a wide variety of financial, statistical, programming and economic issues. Financial subjects covered in the course encompass sources of debt and equity finance for projects, risk analysis of projects, development of covenants and cash flow traps for senior and subordinated debt issues, use of option pricing concepts to measure risk and credit spreads, and credit scoring of project finance debt.
Economic topics deal with pricing of PPA and BOOT contracts, commodity price risk assessment, cost and benefits of political risk insurance multilateral and evaluation of alternative types of risk in projects.
Programming issues addressed in the course include designing macros relevant for project finance models, auditing financial models using a projected balance sheet, resolving circularity associated with debt service reserves, modelling cash flow waterfalls and organising project finance models for effective presentation to investors.
Statistical concepts addressed in the course include measurement of volatility, mean reversion and boundary conditions associated with economic time series and implementation of Monte Carlo simulation in project finance models.
DAY 1 – morning
Introduction and model structure
The course begins with introductory comments about the skills and general objectives in project finance with an emphasis on the difficulty in measuring and valuing risk. After the introductory discussion, participants work on a case involving assessment risks of a project. Issues addressed in the first module include:
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What is the big deal about project finance and what makes project finance different from other forms of financing?
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Where does debt and equity money come from these days in project financing?
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What are the benefits of project finance relative to the high fees received by lawyers and bankers?
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Where has project finance been used and what have been the largest project financings?
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What type of risks should be evaluated in project finance to test when projects go bad?
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What are the financial criteria used to quantify project financings?
Lectures
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Sources of debt and equity finance
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Review of funding and risks in selected project finance transactions
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Key financial metrics in project finance (IRR, DSCR, LLCR and Cash Flow)
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Analysis of a completed project finance model
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Background on risk measurement and financial modeling
Case exercises
DAY 1 – afternoon
Module II:
Debt capacity and debt structure
As described above, the afternoon sessions of the course deal with technical aspects of project finance modelling. The first modelling session covers development of a basic model, given capital expenditures, revenues and expenses.
Issues addressed include: How can we make the models flexible enough to incorporate inevitable delays in construction and alternative retirement dates? What are some of the excel rules that guide accurate and efficient development of models? How can project finance models be audited to check errors that we will make? What should we do to incorporate alternative debt structures and interest during construction into the model?
Lectures
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Comments on spreadsheet style and conventions
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Building block approach to modelling
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Basic mechanics of project finance models
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Separation of construction period from operating period
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Sources and uses of funds statement during the construction period
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Cash flow, net income, equity balance, construction financing and income taxes
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Internal rate of return on the project and central concept of free cash flow
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Construction of a balance sheet and use of a balance sheet in auditing the model
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Interest during construction
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Accounting
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Illustration of impacts in completed model
- Circularity problems
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Exercise 2a: Base model layout and financial Statements without debt (1 hour)
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Exercise 2b: Addition of debt leverage to the basic model (1 hour)
DAY 2 – morning
Module III:
Risk analysis and economic assumptions
Valuation of project finance debt, project finance equity and project finance assets involves projecting cash flows and assessing the risks associated with the cash flows. The risks can often be mitigated through revenue and expense contracts. The most time spent developing project finance models should be to develop economic assumptions in a base case and assessing risks. Module three addresses economic analysis behind key value drivers in a project finance model. A case study is used to develop economic assumptions and to demonstrate use of sensitivity analysis, break-even analysis and tornado diagrams. Issues addressed in this module include: If we sign a contract that changes the risk profile of a project, how should we value the contract? What are the three fundamental drivers of the value of projects? Where should we start in looking for the most important risks? What are examples of risks that have caused major projects to fail such as Eurotunnel, Euro Disney, U.S. merchant electric plants and Enron’s Dabhol LNG plant?
Lectures
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Market risks in project finance
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Capital expenditures
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Forward price
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Volume – capacity utilisation
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Input forward price
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Efficiency
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Operation and maintenance expenses
Contract risks in project finance (BOOT, PPA and other longterm contracts)
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Economic rational for long-term contracts
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Incentive to break contracts
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Relation between cost and revenue contracts
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Example of flexible supply contracts
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Effects of variable supply contracts on cash flow
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Financial risks in project finance
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Interest rate risk
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Hedging of risks
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Exchange rate risk
- Political risk
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Exercise 3a: Computation of price levels in contracts (30 minutes)
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Exercise 3b: Break-even analysis in toll road project finance case with completed model (45 minutes)
DAY 2 – afternoon
Module IV:
Modelling of construction drawdowns and sensitivity analysis
The second modelling session extends the base model to incorporate specific aspects of project financing including construction draw-downs, free cash flow, debt service coverage and LLCR. Issues covered in this module include: What difference does it make that project finance models show construction schedules on a monthly basis? How can we convert annual flows to monthly flows? Are look-up tables really useful in project finance models? How easy is it to incorporate those macros in project finance models? How can I add those tornado diagrams to my project finance model? How can I add features such as conditional formatting and list boxes to the model?
Lectures
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Monthly draw downs and semi annual debt service
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Reports for monthly construction
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Reports for semi-annual debt service
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Analysis of subordinated debt
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Debt sizing Macros
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Basic goal seek Macro
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Working with range names
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Alternative ways to enter data
- Use of range names
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Exercise 4a: Construction profiles and monthly construction (45 minutes)
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Exercise 4b: macro exercise (30 minutes)
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Exercise 4c: Tornado diagrams (1.5 hours)
DAY 3 – morning
Module V:
Debt structuring in project finance
The fifth module addresses debt structuring aspects of project finance including covenants, cash flow traps, senior and subordinated debt issues, collateral and debt capacity. Issues covered include: What type of covenants are included in project
finance transactions? Is it more important to trap cash during good times or develop covenants that prevent cash from leaving the project when times are bad? How much safer is senior debt than junior debt? Should cross defaults be included in the transaction? What is the appropriate level for various covenants and what financial ratios should be used in the covenants?
Lectures
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Debt structure theory and analysis
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Alternative debt repayment structures
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Introduction to debt as a put option
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Cash flow sweeps and traps
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Duration and other debt measures
Covenants in project finance
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Positive and negative covenants
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Project finance covenants versus corporate covenants
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Covenants and risk analysis of projects
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Examples of covenants
Debt capacity analysis in project finance
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Sources of debt financing in project finance
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Amounts of debt leverage for alternative projects
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Senior versus junior debt tranches
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Debt term
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Use of debt service reserves
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Appropriate benchmarks and information
Capital structure theory and project finance objectives
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Miller and Modigliani
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Income taxes
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Bankruptcy monitoring cost
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Information signalling
- Pecking order theory
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Exercise 5a: Eurotunnel financial structure (.5hours)
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Exercise 5b: Evaluation of covenants and senior versus subordinated debt using completed model (45 minutes)
DAY 3 – afternoon
Module VI:
Modelling complex debt features in project finance
The third technical modelling session involves modelling cash flow waterfalls, covenants, defaults and cash traps. Once this part of the model is complete, the IRR on debt can be measured as well as the IRR on equity. Modelling issues include: How can we model inflows and outflows from a debt service reserve? What complications arise from modelling senior and subordinated debt tranches? Can we really quantify the cost and benefits of covenants and cash flow traps? What should we do to the model when a debt payment default occurs?
Lectures
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Debt service reserve accounting and modeling
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Accounting for debt service and other reserves
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Illustration of impacts in project model
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Circularity problems
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Interest income
Modelling defaults on debt service
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Revenue scenarios
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Cash flow waterfall
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Interest after default
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Repayment after default
Modelling covenants and cash flow traps
DAY 4 – morning
Module VII:
Multilateral agencies and project finance credit analysis
One of the features that differentiates project financings from other transactions is that various political risks can be mitigated through procurement of insurance from multilateral agencies. Project financing also involves different methods of risk rating than other corporate credits. The seventh module addresses risk rating and risk mitigation through multilateral agencies. Issues addressed in this section include: What are the benefits and costs of using multilateral agencies? What are the various multilateral agencies that can be used? How do rating agencies assess project finance debt? How can you use project finance models to assign a risk rating?
Lectures
Credit analysis and economic assumptions in models
General discussion of Southport case
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History of the project
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Issues facing the mining projects
- Model and valuation objectives
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Exercise 7a: Economic assumptions and financial structure in Southport case (1.5 hours)
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Exercise 7a: Computation of risk spread in Southport case with alternative debt Structures (1.5 hours
DAY 4 – afternoon
Module VIII:
Technical project finance modelling issues
The afternoon module deals with miscellaneous technical issues that arise in project finance modelling. Subjects include working capital, formatting, use of data tables, depreciation, leases, and resolving circularity. The module will cover further use of macros in modelling as well as financial issues associated with the topics. Issues include: Does it matter that circularity arises in our models? Are data tables worth the hassle in model building? What should be done to include movements of working capital in the model? Can we demonstrate the basic cost and benefits of leases with a relatively simple model?
Lectures
Theory and analysis of leases
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Tax depreciation versus debt repayment
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Tax reasons for using leases
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Formulas for computing lease payments
Accelerated depreciation
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Tax depreciation conventions
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Formulas for computing tax depreciation
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Vintage computations of tax depreciation
Working capital
DAY 5 – morning
Module IX:
Commodity prices and time series analysis in project finance models
Commodity prices affect the value of many projects such as oil and gas projects, electricity projects, refineries and other plants. The seventh module of the course addresses how to use option pricing concepts in valuing project finance debt where the yield spread on risky project finance debt is equated to the premium of a real put option. The exercise teaches attendees how to practically apply real options concepts in project finance modeling and how to develop macros that incorporate data from multiple files.
Lectures
Theory and analysis of real options
Option price analysis
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Payoff structure and premium of options
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Determinants of value in options
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Options in project finance
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Project finance debt as option
Monte Carlo simulation in project finance models
Valuation of risky debt using option pricing models
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Structure of risky debt as an option
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Probability of default and interest rate spread
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Mechanics of equating value of risky debt to risk free debt
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Iterative procedure in deriving required risk spread
Class exercises
- Exercise 9a: Electric plant case study (1.5 hours)
DAY 5 – afternoon
Module X:
Monte Carlo simulation in project finance models
After covering traditional measurement of risk through breakeven and sensitivity analysis, the course moves to mathematical approaches that directly attach a numeric value to risk. Exercises in this part of the course include creation of time series models, Monte Carlo simulation and implementation of option price models. This part of the course addresses how to use option pricing concepts in valuing project finance debt where the yield spread on risky project finance debt is equated to the premium of a real put option. The exercise teaches attendees how to practically apply real options concepts in project finance modelling and how to develop macros that incorporate data from multiple files.
Lectures
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Economics of commodity prices
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Long-term forward prices and economic theory
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Equilibrium production cost
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Productivity changes and resource supply
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Demand changes
Option valuation analysis
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Black-scholes model
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Dynamic programming
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Monte Carlo Simulation
Monte Carlo simulation
Simulation of real option value
Valuation of risky debt using option pricing models
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Structure of risky debt as an option
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Probability of default and interest rate spread
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Mechanics of equating value of risky debt to risk free debt
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Iterative procedure in deriving required risk spread
Class exercises
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Ed Bodmer
Edward Bodmer has created innovative forward pricing, productivity measurement and investment valuation software for consulting clients throughout the United States. He has taught energy economics and finance throughout the world, and formulated significant government policy and corporate strategy in the U.S.
Mr. Bodmer's consulting clients include investment banks, commercial banks, research institutions and government agencies on a wide variety of complex valuation and advisory matters. He has constructed a unique framework for electricity price forecasting and valuation using production cost modelling techniques combined with option price theory and Monte Carlo simulation.
Mr. Bodmer is also an adjunct professor at leading University where he teaches courses in microeconomics. Along with his practical experience that covers a multitude of major advisory projects, he has taught specialised courses in financial modelling, electricity pricing, option valuation, mergers and acquisitions and contracting to investment banks, commercial banks, industrial corporations and electric utility companies.
Mr. Bodmer was formerly Vice President at the First National Bank of Chicago where he directed analysis of energy loans and also created financial modelling techniques used in advisory projects. He has used the models in providing expert testimony on subjects ranging from capital structure to investments in multi-billion dollar nuclear plants to complex valuation of new investments.
Mr. Bodmer received an MBA degree specialising in econometrics (with honours) from the University of Chicago and a BS degree in finance from the University of Illinois (with highest university honours). He has written many articles and is in the process of completing a textbook on valuation of electricity assets.
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