My first book (not yet published) deals with valuation blunders both from a practical perspective and a theoretical perspective. The book addresses theoretical errors made in measuring country and/or political risk for equity and debt; in computing cost of capital from the CAPM and other methods; in using multiples for valuation; in evaluating return requirements for different capital structure; in applying the IRR to long-lived projects and interpreting high IRR's; in attempting to implement real options; in creating time series equations with different volatility and mean reversion parameters and, most importantly, in developing sensible assumptions for financial models. The conceptual problems are discussed in the context of case studies where managers, analysts, bankers and other professionals make recurring errors.

Drafts of various sections from this book are included below.

Send me an e-mail at edwardbodmer@gmail.com

Part 1 - Introduction and Case Studies of Valuation Nightmares

Part 1 reviews various case studies of valuation errors and identifies common threads that recur in valuation analysis related to assuming high levels of earned returns can continue without creating some kind of addiction to products; not understanding the exposure to high levels of fixed costs; making agressive assumptions without using simple benchmark analysis to verify them, relying on experts such as rating agencies, consultants and well renowned executives, believing that investments can earn economic returns because of alternaitve methods of modelling such as real options, not fully investigating the long-term prospects for fundamental assumptions through analysis of marginal cost and believing that earnings multiples or book value multiples can be sustained. The case studies are not intended to encompass all valuation errors. Many bankrupcies and value changes come from obselete products and inept and/or corrupt manangement. The case studies focus on investments and re-structuring including Iridium, Dahbol, Eurotunnel, Constellation Energy, Kitty Hawk Airlines, Quicksilver Resources (shale gas) and the California Electricity Crisis.

This chapter introduces three general frameworks to valuation and then describes a few case histories in which classic valuation mistakes were made by bankers, investors and other financial analysts. The case studies recount situations in which finance professionals either have used valuation techniques that did not adequately consider risks, or they misapplied valuation concepts and analytical models. Although some rather complicated models are presented and a bit of finance theory are discussed, the stories of valuation mistakes emphasize that better human judgment and intelligence with respect to very basic economic principles rather than increased sophistication in analytical techniques is the primary factor that could have avoided most of the valuation errors. The different valuation debacles an obvious but often neglected point that all of the sophisticated financial models, elaborate mathematical representations of risk, application of intricate finance theory and other analytical tools are irrelevant without being supplemented by a healthy dose of wisdom and business sense. Many learned the hard way that risks associated with lending money to a waitress in who puts no money down on a $500,000 house cannot be gauged by running thousands of simulations by a credit analyst at Standard and Poor’s on the 50th floor of an office building in Manhattan.

The importance of benchmarking is emphasized and the necessity of developing bechmarks is emphasised (failure to benchmark). Examples include computing the capacity factor of a solar project, evaluating the return on investment in the context of historyand testing IRR.

Part 2 - Why the IRR does not Measure Value and Expropriation of Money from Developing Countries through Risk Assessment and Mistakes made in Applying Ideas from Science that do Not Belong in Financial Analysis

Part 2 of the book begins the analytical theoretical problems with the way project finance and corporate finance investments are evaluated. Expectations and measurement of IRR is the first issue addressed. Chapter 2 begins with discussion of the all pervasive IRR and why it has so many problems including: (1) not appropriately valuing long-term investments; (2) over penalising investments with so-called country risk; (3) not accounting for changes in risk over time; and (4) not directly measuring risk premiums. The chapter includes discussion of the philosophy of banking and the volatility of the value of investments versus volatility and potential changes in the value of cash flows. Trusting business plans and sales presentations versus real history. What it takes to get a stamp of approval from a bank or a market and why stamps of approval are so important.

Chapter 3 - Risk Assessment and Mistakes made in Applying Ideas from Science that do Not Belong in Financial Analysis

Chapter 3 addresses the philosophy of risk and general appraches to making forecasts for valuation analysis. The notion of being some kind of historian/statistician/fortune teller is the starting point of the analysis. The difference between fancy looking business plans and sales presentations versus real history provides is described in the context of renewable energy analysis. Chapter three addresses risk analysis in valuation by first presenting a variety of practical ways to directly measure risk using traditional sensitivity analysis, scenario analysis, break-even analysis and tornado diagrams. After describing judgmental approaches to risk analysis requiring judgment with respect to prospective economic variables, the remainder of the chapter focuses on use of time series models as the basis for mathematical quantification of risk – equations developed from statistical parameters such as volatility, mean reversion, price boundaries, industry productivity trends, correlation between variables and jump processes. Development of time series equations as part of the valuation process can appear very attractive because the equations can be used to compute statistics such as value at risk, probability distribution of equity returns and minimum required credit spreads. The discussion notes that while time series models can become addictive in seeming to provide answers to many financial problems such as deriving the probability of achieving returns for assets with different risk characteristics, the mathematical techniques can also be useless if statistics are used without explicitly considering the economic fundamentals that underlie the mathematical equations. Because of problems with application of historic data in construction of time series model parameters, the chapter explains how to construct time series equations using economic theory together with business judgment that allows for dramatic deviations between historic statistical data and prospective distributions.

Chapter 4 - Attempts to Quantify Risk using Cost of Captial and Distortions in the Capital Asset Pricing Model

Chapter four moves to the question of converting risk into value. The discussion covers various different investment valuation techniques that compute the value of an investment given the riskiness of cash flows. Different approaches that apply the theory of finance, that use financial market data, and that extend option pricing theory to measure risk are presented. The chapter begins by reviewing traditional discounted free cash flow and cost of capital analysis. This demonstrates that the typical discounted cash flow techniques taught in business schools fail when it comes to most practical investment decisions. Next, an alternative way to translate cash flow risk into value is described which uses debt capacity to evaluate equity returns. The information source for the debt capacity analysis is financial criteria from bankers and credit rating agencies in asset and equity valuation. Because bankers and credit rating analysts are people who supposedly measure risk and to quantify the overall risk of an investment, valuation techniques derived from debt capacity should be superior to theoretical analyses using the capital asset pricing model which is founded on un-measurable parameters and is subject to bias. That is as long as bankers are doing their job. In fact, bankers and credit rating agencies have not had a stellar record in assessing risk. Because of this, a third method of translating cash flow into value is introduced that uses synthetic debt capacity measurement and time series analysis. This method simulates the theoretical debt capacity of a project through evaluating the probability of default and loss given default derived from time series parameters and Monte Carlo simulation. Once the theoretical debt capacity is established, the value of an investment can be derived through establishing a minimum rate of return as with the method that uses benchmark ratios from bankers and credit rating agencies.

Chapter 5 - Inappropriate Attempts to Overstate Value using Real Options in Valuation

Chapter five considers the question of whether option pricing models can realistically be applied to real world capital investment and budgeting decisions. This is not the perfunctory option modelling chapter that seems to be part of any finance text these days. In working through the question of whether option models are really useful, emphasis is placed on practical issues involving the lack of the ability to hedge, mean reversion in cash flow, undefined exercise prices and required management action. These factors create a large gap between plugging in option pricing formulas and applying option theory in a practical manner to measure the value of real investments. The practical issues are illustrated using real options to delay development of an investment, cancel construction of a plant, cease operation, mothball and retire a plant by using different volatility, mean reversion, price boundary and correlation parameters. Monte Carlo analysis that accounts for the mean reversion and the specific operation of plants are compared to option models such as the Black-Scholes equation. At the end of the chapter, option concepts are applied to measurement of the value associated with a company being the “provider of last resort” where long-term capacity contracts exist along side customer options to switch suppliers when market prices fall.

Chapter 6 - Multiples, Terminal Value and DCF Complexities

Chapter six describes practical [[#|application]] of valuation analysis using multiples such as the price to earnings (P/E) ratio and the enterprise value to the EBITDA (EV/EBITDA) ratio as well as detailed issues associated with the discounted cash flow model. This chapter is not like a typical textbook treatment of discounted cash flow analysis that describes how to compute free cash flow and then add the terminal value and discount the cash flow at the WACC. Instead, the chapter explains theoretical and simple mathematical flaws in the way simple weighting of debt and equity is computed in the WACC; it describes flaws in how betas are un-levered and then re-levered and it explains why the cost of equity does not necessarily increase for highly leveraged companies due to call option characteristics of equity capital. The chapter explains how to establish drivers that explain why a P/E ratio, an EV/EBITDA ratio or a market to book ratio should be at a given level. Finally the chapter bridges the very wide gap between theory and practice in applying the discounted cash flow model. Real world problems addressed include determining stable relationships between depreciation and capital expenditures, treatment of deferred taxes and long-run estimates of changes in deferred taxes, consistency between working capital changes and growth rates, use of multiples in computing terminal values and other issues.

Chapter 7 - Development of Long-term and Short-term Price Forecasts in Valuation Analysis

Whether it be through government support, contracts developed by lawyers who charge thousands of dollars per hour, through advertising that creates addictions to products, the assumption that prices can remain above the cost of production for an industry is a dangerous way to make long-term projections. Part 7 explains how to evaluate supply curves and the cost of production in an objective manner. The discussion begins with explanation of how companies desire to explain how they have unique advantages that enable them to maintain prices above the cost of production and earn returns higher than their cost of captial. Examples where earned returns are very high including the cable industry are described.

## I will deal with the Expiration of Wikispaces -- I can now make a better website.

## Re-write of Finance Theory Text with Case Studies

## My first book (not yet published) deals with valuation blunders both from a practical perspective and a theoretical perspective. The book addresses theoretical errors made in measuring country and/or political risk for equity and debt; in computing cost of capital from the CAPM and other methods; in using multiples for valuation; in evaluating return requirements for different capital structure; in applying the IRR to long-lived projects and interpreting high IRR's; in attempting to implement real options; in creating time series equations with different volatility and mean reversion parameters and, most importantly, in developing sensible assumptions for financial models. The conceptual problems are discussed in the context of case studies where managers, analysts, bankers and other professionals make recurring errors.

## Drafts of various sections from this book are included below.

## Part 1 - Introduction and Case Studies of Valuation Nightmares

## Part 1 reviews various case studies of valuation errors and identifies common threads that recur in valuation analysis related to assuming high levels of earned returns can continue without creating some kind of addiction to products; not understanding the exposure to high levels of fixed costs; making agressive assumptions without using simple benchmark analysis to verify them, relying on experts such as rating agencies, consultants and well renowned executives, believing that investments can earn economic returns because of alternaitve methods of modelling such as real options, not fully investigating the long-term prospects for fundamental assumptions through analysis of marginal cost and believing that earnings multiples or book value multiples can be sustained. The case studies are not intended to encompass all valuation errors. Many bankrupcies and value changes come from obselete products and inept and/or corrupt manangement. The case studies focus on investments and re-structuring including Iridium, Dahbol, Eurotunnel, Constellation Energy, Kitty Hawk Airlines, Quicksilver Resources (shale gas) and the California Electricity Crisis.

## Case Studies

## This chapter introduces three general frameworks to valuation and then describes a few case histories in which classic valuation mistakes were made by bankers, investors and other financial analysts. The case studies recount situations in which finance professionals either have used valuation techniques that did not adequately consider risks, or they misapplied valuation concepts and analytical models. Although some rather complicated models are presented and a bit of finance theory are discussed, the stories of valuation mistakes emphasize that better human judgment and intelligence with respect to very basic economic principles rather than increased sophistication in analytical techniques is the primary factor that could have avoided most of the valuation errors. The different valuation debacles an obvious but often neglected point that all of the sophisticated financial models, elaborate mathematical representations of risk, application of intricate finance theory and other analytical tools are irrelevant without being supplemented by a healthy dose of wisdom and business sense. Many learned the hard way that risks associated with lending money to a waitress in who puts no money down on a $500,000 house cannot be gauged by running thousands of simulations by a credit analyst at Standard and Poor’s on the 50th floor of an office building in Manhattan.

## The importance of benchmarking is emphasized and the necessity of developing bechmarks is emphasised (failure to benchmark). Examples include computing the capacity factor of a solar project, evaluating the return on investment in the context of historyand testing IRR.

Chapter 1 Excel Models

## Part 2 - Why the IRR does not Measure Value and Expropriation of Money from Developing Countries through Risk Assessment and Mistakes made in Applying Ideas from Science that do Not Belong in Financial Analysis

## Part 2 of the book begins the analytical theoretical problems with the way project finance and corporate finance investments are evaluated. Expectations and measurement of IRR is the first issue addressed. Chapter 2 begins with discussion of the all pervasive IRR and why it has so many problems including: (1) not appropriately valuing long-term investments; (2) over penalising investments with so-called country risk; (3) not accounting for changes in risk over time; and (4) not directly measuring risk premiums. The chapter includes discussion of the philosophy of banking and the volatility of the value of investments versus volatility and potential changes in the value of cash flows. Trusting business plans and sales presentations versus real history. What it takes to get a stamp of approval from a bank or a market and why stamps of approval are so important.

## Chapter 2 Page

## Chapter 3 - Risk Assessment and Mistakes made in Applying Ideas from Science that do Not Belong in Financial Analysis

## Chapter 3 addresses the philosophy of risk and general appraches to making forecasts for valuation analysis. The notion of being some kind of historian/statistician/fortune teller is the starting point of the analysis. The difference between fancy looking business plans and sales presentations versus real history provides is described in the context of renewable energy analysis. Chapter three addresses risk analysis in valuation by first presenting a variety of practical ways to directly measure risk using traditional sensitivity analysis, scenario analysis, break-even analysis and tornado diagrams. After describing judgmental approaches to risk analysis requiring judgment with respect to prospective economic variables, the remainder of the chapter focuses on use of time series models as the basis for mathematical quantification of risk – equations developed from statistical parameters such as volatility, mean reversion, price boundaries, industry productivity trends, correlation between variables and jump processes. Development of time series equations as part of the valuation process can appear very attractive because the equations can be used to compute statistics such as value at risk, probability distribution of equity returns and minimum required credit spreads. The discussion notes that while time series models can become addictive in seeming to provide answers to many financial problems such as deriving the probability of achieving returns for assets with different risk characteristics, the mathematical techniques can also be useless if statistics are used without explicitly considering the economic fundamentals that underlie the mathematical equations. Because of problems with application of historic data in construction of time series model parameters, the chapter explains how to construct time series equations using economic theory together with business judgment that allows for dramatic deviations between historic statistical data and prospective distributions.

## Chapter 4 - Attempts to Quantify Risk using Cost of Captial and Distortions in the Capital Asset Pricing Model

## Chapter four moves to the question of converting risk into value. The discussion covers various different investment valuation techniques that compute the value of an investment given the riskiness of cash flows. Different approaches that apply the theory of finance, that use financial market data, and that extend option pricing theory to measure risk are presented. The chapter begins by reviewing traditional discounted free cash flow and cost of capital analysis. This demonstrates that the typical discounted cash flow techniques taught in business schools fail when it comes to most practical investment decisions. Next, an alternative way to translate cash flow risk into value is described which uses debt capacity to evaluate equity returns. The information source for the debt capacity analysis is financial criteria from bankers and credit rating agencies in asset and equity valuation. Because bankers and credit rating analysts are people who supposedly measure risk and to quantify the overall risk of an investment, valuation techniques derived from debt capacity should be superior to theoretical analyses using the capital asset pricing model which is founded on un-measurable parameters and is subject to bias. That is as long as bankers are doing their job. In fact, bankers and credit rating agencies have not had a stellar record in assessing risk. Because of this, a third method of translating cash flow into value is introduced that uses synthetic debt capacity measurement and time series analysis. This method simulates the theoretical debt capacity of a project through evaluating the probability of default and loss given default derived from time series parameters and Monte Carlo simulation. Once the theoretical debt capacity is established, the value of an investment can be derived through establishing a minimum rate of return as with the method that uses benchmark ratios from bankers and credit rating agencies.

Chapter 4 Excel Models

## Chapter 5 - Inappropriate Attempts to Overstate Value using Real Options in Valuation

Chapter five considers the question of whether option pricing models can realistically be applied to real world capital investment and budgeting decisions. This is not the perfunctory option modelling chapter that seems to be part of any finance text these days. In working through the question of whether option models are really useful, emphasis is placed on practical issues involving the lack of the ability to hedge, mean reversion in cash flow, undefined exercise prices and required management action. These factors create a large gap between plugging in option pricing formulas and applying option theory in a practical manner to measure the value of real investments. The practical issues are illustrated using real options to delay development of an investment, cancel construction of a plant, cease operation, mothball and retire a plant by using different volatility, mean reversion, price boundary and correlation parameters. Monte Carlo analysis that accounts for the mean reversion and the specific operation of plants are compared to option models such as the Black-Scholes equation. At the end of the chapter, option concepts are applied to measurement of the value associated with a company being the “provider of last resort” where long-term capacity contracts exist along side customer options to switch suppliers when market prices fall.

## Chapter 6 - Multiples, Terminal Value and DCF Complexities

## Chapter 7 - Development of Long-term and Short-term Price Forecasts in Valuation Analysis

## Whether it be through government support, contracts developed by lawyers who charge thousands of dollars per hour, through advertising that creates addictions to products, the assumption that prices can remain above the cost of production for an industry is a dangerous way to make long-term projections. Part 7 explains how to evaluate supply curves and the cost of production in an objective manner. The discussion begins with explanation of how companies desire to explain how they have unique advantages that enable them to maintain prices above the cost of production and earn returns higher than their cost of captial. Examples where earned returns are very high including the cable industry are described.

Exercises for Chapter 7