Corporate and Project Finance Modeling

Theory and Practice

Edward Bodmer

• Publisher: Wiley
• Year: 2014
• Print ISBN: 9781118854365
• eBook ISBN: 9781118854457
• Edition: 1
• Topic: Business
• Subtopic: Finance
• Index: Business

A clear and comprehensive guide to financial modeling and valuation with extensive case studies and practice exercises

Corporate and Project Finance Modeling takes a clear, coherent approach to a complex and technical topic. Written by a globally-recognized financial and economic consultant, this book provides a thorough explanation of financial modeling and analysis while describing the practical application of newly-developed techniques. Theoretical discussion, case studies and step-by-step guides allow readers to master many difficult modeling problems and also explain how to build highly structured models from the ground up. The companion website includes downloadable examples, templates, and hundreds of exercises that allow readers to immediately apply the complex ideas discussed.

Financial valuation is an in-depth process, involving both objective and subjective parameters. Precise modeling is critical, and thorough, accurate analysis is what bridges the gap from model to value. This book allows readers to gain a true mastery of the principles underlying financial modeling and valuation by helping them to:

• Develop flexible and accurate valuation analysis incorporating cash flow waterfalls, depreciation and retirements, updates for new historic periods, and dynamic presentation of scenario and sensitivity analysis;
• Build customized spreadsheet functions that solve circular logic arising in project and corporate valuation without cumbersome copy and paste macros;
• Derive accurate measures of normalized cash flow and implied valuation multiples that account for asset life, changing growth, taxes, varying returns and cost of capital;
• Incorporate stochastic analysis with alternative time series equations and Monte Carlo simulation without add-ins;
• Understand valuation effects of debt sizing, sculpting, project funding, re-financing, holding periods and credit enhancements.

Corporate and Project Finance Modeling provides comprehensive guidance and extensive explanation, making it essential reading for anyone in the field.

Part I
Financial Modeling Structure and Design
Structure and Mechanics of Developing Financial Models for Corporate Finance and Project Finance Analysis

Chapter 1
Financial Modeling and Valuation Nightmares
Problems That Financial Models Cannot Solve

An inevitable step in just about any financial analysis these days is making some kind of explicit or implicit projection of cash flow and/or earnings and/or financial ratios that measure profitability, credit quality, or other key performance indicators. Since valuation of debt or equity is all about making forecasts, you could go to a fortune-teller or read the astrology section of your newspaper to make a prediction about the future. These days, however, forecasts used in valuation are more often founded on fancy financial models built using elaborate spreadsheets. After the East Asian crisis of 1997, the bursting of the dot-com bubble in 2000, the global financial crisis of 2008, the European debt crisis in 2010, and innumerable other less famous valuation disasters or missed investment opportunities where debt and equity valuation failures had relied on sophisticated financial models, it could be argued that going to astrologers and fortune-tellers would have been a better strategy.

Notwithstanding serious questions about the general efficacy of making financial projections and the dangerous ways in which people make forecasts, the fact is that financial models are becoming more and more complex and they are also being used more than ever before in all types of investment analysis. Seemingly sophisticated financial models using elaborate programming functions can appear impressive and even artistic. But these beautiful models are also often almost impossible to use in assessing risk and value. Given the prominence of modeling in financial analysis, the first part of this book describes how to build flexible, accurate, structured, and transparent financial models that can be used to assess various different valuation problems.

When studying many valuation mistakes made in the past decades, it becomes clear very quickly that the most important pitfall in modeling is the development of economic assumptions for prices, volumes, capital expenditures, and operating expenses that are put into the models. The problems did not happen because of making a spreadsheet that did not follow some bureaucratic best practice defined by some IT staff. If you take a step back and think about all sorts of past financial failures ranging from the global financial crisis to bankruptcies of small business enterprises to industry-specific failures such as solar panel manufacturers, there are a few patterns of mistakes that are repeated and that seem obvious after the fact. Before delving into sophisticated mathematical equations, spreadsheet techniques, and model structure issues that deal with methods to resolve difficult project and corporate finance modeling challenges, you should think about why the outcomes of financial analysis using financial models sometimes fail so miserably. You can then leave these ideas somewhere in the back of your brain while you create the ornate models that follow all of the rules about flexibility, accuracy, structuring, and transparency.

Some recurring valuation mistakes related to financial modeling that continue to be made despite more and more sophistication in financial analysis include the following nine errors:

1. Making assumptions in financial models that business entities earning a rate of return substantially higher than their cost of capital and growing quickly can continue this financial performance for a long time even when they do not have some kind of sustained competitive advantage.

Earning a higher return than the cost of capital and growing quickly seems to put a company in the famous powerhouse square shown on management consultant PowerPoint slides, which is supposedly the best place to be for valuation. But when returns and growth are high, valuations are also high. More important, other companies from all over the world will attempt to enter the industry no matter how unique managers of the company claim to be. New capital expenditures from other companies entering the market then lead to industrywide overcapacity, followed by reduced prices and sudden dramatic declines in returns. If demand growth is slower than expected, which happens more often than not, the overcapacity and depressed prices can last for many years and the company suddenly finds itself in the worst box on those management consulting slides. Examples of high growth and returns leading to industry expansion followed by surplus capacity and price crashes include the famous telecom industry meltdown in the late 1990s, in which more than 50 percent of loans defaulted; the merchant electric power crash of 2000–2001 in the United Kingdom, where virtually every electricity plant without a fixed price contract defaulted on its debt; the real estate industry during many periods, most notably before the U.S. crash of 2008; very high returns earned by solar manufacturing companies, followed by massive new entry and dramatic price declines after Chinese manufacturers entered the industry; high returns earned by bulk cargo vessels before 2008, followed by overcapacity and depressed prices that have continued long after commodity prices and other industries recovered; and depressed occupancy rates and room rates for hotels in Iquitos, Peru, following a period of overbuilding that was initiated when the region received UNESCO heritage site status.

2. Entering projected prices in financial models that remain above the long-run cost of production even when capacity is increasing in an industry.

You can define a bubble as a situation in which prices are above long-run marginal cost and/or asset values are not consistent with levels that provide investors with a reasonable return on their investment. Assuming that prices can be sustained above marginal cost is an error that has happened before the U.S. real estate crash, when people believed they could profit by buying and selling (or flipping) a product. It occurred during the famous tulip bubble in Holland in the seventeenth century, and it may be happening in U.S. natural gas prices above the marginal cost of producing shale gas. The assumption that prices could remain above marginal cost was behind the valuation mistakes just discussed in comparing returns to the cost of capital, ranging from the telecom industry crash to overproduction of container ships.

3. Using information in financial models that relies on so-called independent experts, whether these people or institutions are credit rating agencies, large and reputable corporations, consulting companies that create very fancy models, experts speaking on CNBC or Bloomberg, famous finance professors, or former politicians.

Many valuation nightmares have demonstrated after the fact that it is more important to put your feet on the ground by visiting countries, meeting with real consumers, trying out products and services, and having a thorough independent understanding of the business idea than to trust on so-called experts when developing financial projections. Reliance on entities like rating agencies not only was a cause of the global financial crisis of 2008, but has also occurred with traffic studies made for project financings such as the Eurotunnel; toll roads and toll bridges all over the world; theme parks; and the Iridium disaster, in which Motorola promoted its satellite phones; and countless other cases. The famous Panama Canal catastrophe in which French investors lost so much money in the nineteenth century resulted from trusting the opinion of a famous engineer who had visited Panama only once. Relying on the reputations of companies that were thought to be the most innovative in their industry—such as Enron, WorldCom, and Lehman Brothers—without thinking through the fundamental competitive advantages and product quality has turned out to be very dangerous.

4. Trusting financial model results where increasing returns are projected by management, but not recognizing that the projected returns come about only because the company is taking on increased risks.

Companies with declining returns or lower margins than their peers often desperately try to increase or maintain equity returns. But these companies (or individuals) can generally meet their return objectives only by incurring increased risks and then trying to hide those risks using the latest business jargon and/or creative accounting. When taking on new ventures or deploying capital that involves taking greater risk, it is tempting for management to directly or indirectly cover up the risks through not fully disclosing things or worse, by using very sophisticated and confusing financial terms along with financial models that are impossible to understand. Examples of valuation errors caused by presenting confusing information include Constellation Energy in 2006–2008, Enron's impossible to understand financial statements, and innumerable financial institutions that made risky loans or engaged in risky trading behavior to boost their returns before the financial crisis of 2008.

5. Ignoring shifts in the cost structure and demand changes that can quickly render existing assets obsolete when developing risk analysis using financial models.

Sudden shifts in demand and/or price is a particular problem in modeling oligopolistic...

Table of contents

• Cover
• Title Page
• Copyright
• Preface
• Acknowledgments
• Part I: Financial Modeling Structure and Design
• Part II: Analyzing Risks with Financial Models
• Part III: Advanced Corporate Modeling: Modeling Terminal Value with Stable Ratios in the Discounted Cash Flow Model, Deriving Implied Multiples, and Computing the Bridge between Equity Value and Enterprise Value
• Part IV: Complex Issues: Circular References and Other Complex Issues from Financial Structuring in Project Finance and Corporate Finance Models
• About the Author
• About the Website
• Index
• End User License Agreement