Equity Valuation, Risk, and Investment: A Practitioner's Roadmap

By Peter C. Stimes

Author Peter Stimes’s analysis of the investment process has long been inspired by some of the best minds in the world of finance, yet some of the ways in which he approaches this discipline are truly unique. In Equity Valuation, Risk, and Investment, Stimes shares his extensive expertise with you and reveals how practitioners can integrate and apply both the theory and quantitative analysis found in finance to the day-to-day decisions they must make with regard to important investment issues.

• Language: English
• Publisher: Wiley
• Release date: Jul 22, 2011
• ISBN: 9781118160756

Book preview

Contents

Foreword

Preface

About the Author

Chapter 1: Introduction

Theoretical Precision or Theoretical Resilience?

Practical Difficulties as Well

Overview of Our Analysis

A Quick and Important Note on Mathematical Notation

Chapter 2: Inflation-Protected Bonds as a Valuation Template

Formulas behind the Intuition

TIPS versus Traditional Fixed-Rate Bonds: Measuring the Differences

A Peek Ahead

Chapter 3: Valuing Uncertain, Perpetual Income Streams

Mathematical Development of Unleveraged Firm Valuation

What Does the Valuation Formula Tell Us about Sensitivity to Inflation?

Sensitivity to Real Discount Rates and Growth Factors

Comparison with a Traditional Model of Firm Valuation

Chapter 4: Valuing a Leveraged Equity Security

Leverage in the Presence of Corporate Income Taxes

From Theory to Practice

Chapter 4 Supplement: Relationship between Leveraged Equity Discount Rate and Debt-to-Capital Ratio for Highly Leveraged Companies

Chapter 5: Case Studies in Valuation During the Recent Decade

Case 1: Coca-Cola

Case 2: Intel

Case 3: Procter&Gamble

Market-Implied, Inflation-Adjusted Discount Rates for Coca-Cola, Intel, and Procter&Gamble

Case 4: Enron

Tying Up the Package: Practical Lessons from All Four Cases

Chapter 6: Treatment of Mergers and Acquisitions

Generalizing from the P&G/Gillette Example

Applicability of the Results under Alternate Merger Terms

Analytical Postscript 1: Common Stock Buybacks and Issuances Outside the Merger Framework

Analytical Postscript 2: A Word on Executive Stock Option Grants

Chapter 7: A Fair Representation? Broad Sample Testing over a 10-Year Market Cycle

Sample Descriptive Data

Basic Valuation Results

Predictive Strength of the Model for the Whole Period

Predictive Strength of the Model for Subperiods

Chapter 8: Price Volatility and Underlying Causes

Deriving the Formula for Price Changes

Translating the Price Change Formula into Volatility Estimates

Digression: Impact of Debt Leverage on Equity Volatility

Obtaining the Volatility of the Underlying Variables

Chapter 9: Constructing Efficient Portfolios

Extracting Expected Equity Returns from Observed Price/Earnings Ratios: Part I

Extracting Expected Equity Returns from Observed Price/Earnings Ratios: Part II

Extracting Expected Equity Returns from Observed Price/Earnings Ratios: Part III

Creating Efficient Portfolios: Unconstrained Case

Creating Efficient Portfolios: Case Where Asset Weights Are Required to Be Nonnegative

Computing the Variance/Covariance Matrix Inputs

Chapter 10: Selecting among Efficient Portfolios and Making Dynamic Rebalancing Adjustments

Reconciling Portfolio Desirability and Feasibility

Turning Theory into Easily Calculated Results

Adjusting for Changes in Long-Term Expected Returns on Common Equity

Adapting to More General Changes in Risk-Adjusted Expected Returns

Recapitulation and an Important Caveat

Chapter 11: How Did We Arrive Here Historically? Where Might We Go Prospectively?

Crises of Confidence

Some Answers Begin to Emerge

What If Everyone Followed This Type of Model and Investing?

Next Steps

Appendix A: Mathematical Review of Growth Rates for Earnings, Dividends, and Book Value per Share

Appendix B: Sustainable and Nonsustainable Inflation Rates

Appendix C: Deriving the Equity Duration Formula

Appendix D: Traditional Growth/Equity Valuation Formula

Appendix E: Adjustments Required to the Traditional Growth/Equity Valuation Formula to Preserve Inflation Neutrality

Appendix F: Brief Recapitulation of the Miller 1977 Capital Structure Irrelevance Theorem

Appendix G: Time Series Charts of Unleveraged, Inflation-Adjusted Discount Rate Estimates

Appendix H: Comparison of Volatility of Pretax and After-Tax Income

Appendix I: Relationship between Observed Price-to-Earnings (P/E) Ratios and Nominal Interest Rates

Appendix J: Additional Background on Mathematical Optimization Subject Constraint Conditions

Appendix K: Derivation of Asset Class Covariances

Appendix L: Expected Return and Variance/Covariance Inputs Underlying Portfolio Examples

Bibliography

Index

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Copyright © 2008 by Peter C. Stimes. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data

Stimes, Peter C., 1955–

Equity valuation, risk, and investment: a practitioner’s roadmap / Peter C. Stimes.

p. cm. – (Wiley finance series)

Includes bibliographical references and index.

ISBN 978-0-470-22640-7 (cloth)

1. Corporations-Valuation. 2. Securities-Valuation. 3. Risk. 4. Portfolio management. 5. Investment analysis. I. Title.

HG4028.V3S85 2008

332.63’2-dc22

2007031889

To the One Whose Love for Me Is Beyond Measure

Foreword

Pete Stimes has written a remarkable book. This comes as no surprise because Pete Stimes is a remarkable guy. He has the broad perspective of a history major—which he is—and the keen analytical and mathematical skills of a professional quantitative investment analyst—which he also is. His analysis of the investment process draws heavily on the work of many of the leading lights in the field, such as Martin Leibowitz, Merton Miller, Eugene Fama, and others, but some of the ways in which he puts the pieces of the puzzle together are uniquely Pete’s. Serious students of finance will gain new insights from this book.

Almost 50 years ago, my first mentor gave me an incredibly useful and durable insight into investment management. As he put it, It ain’t what you don’t know that gets you. It’s what you know that ain’t so. The investment management field has gone through a dramatic transformation in the last half century, which is described very well in the final chapter of this book. An evolutionary process such as this inevitably adds to our conventional wisdom a few things that ain’t so.

For example, consider the issue of the impact of inflation on common stocks. In the period following World War II, everyone knew that common stocks are a hedge against inflation, and the market seemed to validate this belief. Then came the late 1970s and early 1980s, when rampant inflation and soaring interest rates crushed the stock market, showing that inflation can be harmful to stocks. Is it possible that something here ain’t so? This apparent contradiction actually makes sense within the context of the refined analytical framework that Pete introduces in this book.

The heart of Pete’s work involves analyzing equities after the effects of inflation. We have long looked at nominal interest rates as being the sum of a real, or inflation-adjusted, interest rate and an additional component to compensate for inflation. The introduction of Treasury Inflation Protected Securities (TIPS) created an actual market based on risk-free real interest rates that behaves very differently from traditional Treasury bonds paying nominal interest rates. What is to keep us from conceptually looking at equities in the same light? Pete shows us how enlightening that can be.

Pete is a masterful builder of economic and financial models. His book allows the reader to strap himself or herself into the copilot’s seat and to participate in each step of Pete’s thinking as he models the investment process. The model is totally transparent, and, beyond that, it is extraordinarily comprehensive. Unlike some automobile mechanics, Pete does not end up with a handful of unexplained parts left over when he is done.

Pete’s background as a practitioner is also evident in the book. He believes that a model is useful only if an analyst can actually get the necessary input data and run the model without letting the perfect be the enemy of the possible. He avoids cumbersome, precise calculations of data that can be approximated fairly easily without significantly changing the model’s ultimate conclusions. As Pete expresses it, he would rather be approximately correct than precisely wrong.

Some might ask, Why bother with an investment model? After all, aren’t models just ‘garbage in, garbage out’? Maybe so, but that misses the point. Modeling forces the analyst to consider and understand all the moving parts of a problem. Some of the inputs require difficult estimates, but such estimates are already implicit in market prices. A good model will identify the most critical estimates and allow the user to test the impact of changes in them. Such a model will also chastise its creator if the underlying assumptions are not consistent. The bottom line is that models, most of all, are about intellectual discipline.

In building the model, Pete has steered away from reliance on book values, earnings, and dividends, which are susceptible to changes in accounting policies, recapitalizations, dividend policies and other forms of restructurings, management actions, and, possibly, skullduggery. Instead, the model places heavy reliance on cash flow, the portion of cash flow likely to be invested in true growth (as opposed to maintenance) of the business, and the after-inflation rate of return likely to be earned on such investments in growth projects.

I personally found Pete’s inputs of the portions of cash flow to be invested for true growth by individual companies and the real rates of return on such investments rather surprising. He suggests that for most large companies, such investments will earn about the same rate of return, which is determined by competitive conditions. The difference between high-growth companies and slower growers lies mainly in the number of such investment opportunities, rather than in the returns earned. It makes sense! Every good model produces some eye-openers, and this was one for me.

In keeping with the spirit of discipline, Pete requires the inputs to the model to be consistent with measures of the overall economy. Obviously, a large group of companies is not likely to grow at some multiple of the growth rate of the economy as a whole (even though adding up various analysts’ estimates often gives a different impression!). One would expect that such forcing of the foot to fit within the shoe would cause the model to detect general overvaluation in a period of irrational exuberance. It appears to have done just that.

Nothing in the model reduces the need for diligent oversight through good old-fashioned security analysis. Pete is the first to concede that actual market prices may drift only gradually over time toward the very fundamental valuations produced by the model and that unanticipated events (such as mergers, acquisitions, business shocks, etc.) can intervene. His analysis also recognizes that, even when the model is right on, there will be volatility of actual market prices, driven primarily by the volatility of operating cash flow and, to a lesser extent, shifts in the discount rate (after inflation) implied by the market price. In short, we still need to know well the companies in which we invest.

So, at the end of the day, how does Pete’s work fit into the real-life world of investment managers? Those who are trying to beat the market at every turn may have a problem with the sluggish correction by the market for the over- and undervaluations revealed by the model. For the rest of us, however, the persistence of those discrepancies looks more like an opportunity. For all of us, it is comforting to have the anchor of a solid understanding of the fundamental investment valuation process that the book provides.

Robert T. Flaherty, CFA

Cofounder, Flaherty & Crumrine Incorporated

Preface

Thomas Edison once was asked if he was disappointed by the huge number of failures he experienced on his way toward developing the light bulb. He is said to have replied that these were not failures at all. Each was, after all, a step in weeding out all that would not work in the creation of the final product.

Similarly, this book is mainly the result of many things that ultimately did not work to my satisfaction during my professional career. Early on, I became frustrated with historic price-to-earnings (P/E) analysis. There was, for a start, no objective basis to ascertain what reasonable P/Es should be. Furthermore, the uncharacteristic inflation of the late 1970s and early 1980s introduced complexities that seemed outside the range of P/Es historically experienced. To make things worse, the formation of the Financial Accounting Standards Board (FASB) in the 1970s was the harbinger of countless revisions of accounting rules, the end result being that intertemporal comparisons of earnings over long, historical market periods became problematic in the extreme.

The microchip revolution and the accessibility of cheap computing power in the early 1980s held out the possibility that dividend discount models (DDMs) would provide a systematic basis for evaluating common equities. However, for most companies, the net present value attributable to near- and intermediate-term dividend flows was not significant. Instead, the major contributor to net present valuation was the growth rate of dividends. This, in turn, reflected a complex interaction between and among achievable returns on book equity, dividend payout ratios, common stock issuance/repurchases, profitability of retained earnings, and targeted debt leverage. With powerful computers finally in our grasp, we in the financial analyst profession suffered frustrations as we saw just how intractable these multiple interactions could be. Furthermore, the analyst community lacked consensus on the interaction between nominal cash flow discount rates and long-term corporate cash flow generation capacity. Without some measure of common, historical sense, our profession’s green-bar, dot-matrix printer output thus frequently became the embodiment of the GIGO principle: garbage in, garbage out.

As the 1980s progressed, I was increasingly exposed to proposed investments where implicit or explicit debt leverage greatly increased prospective returns, but where the impact on the ultimate risk of the investment was difficult to ascertain. While the fledgling field of financial derivatives analysis had great success during this time in analyzing the interactions between debt and underlying asset volatility, the field of equity valuation did not appear to have nearly the same degree of success. In fact, while there was a great deal of study of equity volatility reflected in historical price series and while there was a fair degree of research on equity valuation, I was dissatisfied that there was little useful linkage between the two topics. The two hemispheres of the profession’s brain were not communicating well with each other.

In any event, at the beginning of the 1990s, I was called away to a long sojourn in fixed-income land. This entailed a turning of attention away from equities and toward credit quality, financial derivatives, and related quantitative analysis during more than 15 years at Flaherty & Crumrine. While questions about equity analysis naturally receded from the forefront of my research, they never completely vanished. After all, successful credit analysis is impossible without having at least some intuitive sense for equity analysis.

My years at Flaherty & Crumrine turned out to be a textbook case of the principle that creativity is what occurs when you are busy doing something else. The creative process must have started when I applied my equity-analysis skills toward the practice of fixed income analysis. Notably, the understanding of a company’s nonquantitative story or strategic outlook turned out to be surprisingly useful when applied to the application of uniform, statistical measures of credit strength typical of fixed-income analysis. On the flip side, what was apparently happening simultaneously in the unconscious, creative recesses of my mind was the taking of the quantitative, yield-spread valuation approach from fixed-income analysis and finding a way to apply it to the touchy-feely, less numerical world of stock picking. At the same time, my extensive involvement with financial futures and options was creating a deeper understanding of financial arbitrage valuation principles. The recesses of my mind were to transform this into a way to value common equities as simply the residual value of any firm after subtracting out today’s market value of debt liabilities.

Gone was the need to project earnings per share, prospective leverage policies, share repurchase plans, and dividend policies. If one could reasonably conclude, as Nobel laureate Merton Miller proposed in a seminal 1977 article, that the total valuation of any individual firm was not affected by the degree of leverage, then a fundamental arbitrage approach could achieve, by a flanking maneuver, what could not be attained by a daunting frontal assault using traditional projection techniques. The only other remaining major ingredients necessary for the new valuation recipe were (1) the mathematics of inflation-adjusted cash flows, which I developed as a by-product of my need to analyze the newly issued Treasury Inflation Protected Securities (TIPS) in the later 1990s, and (2) some ability to break down the value of an enterprise, along the lines proposed by Martin Leibowitz, into a tangible value attributable to current net cash flows and a franchise value arising from the ability profitably to reinvest net cash flow into positive net-present-value projects.

With my retirement from Flaherty & Crumrine, I finally had the leisure to do two things: spend the day watching stock jockeys on CNBC playing the quarterly earnings beat consensus game or organize my thoughts into a consistent and coherent analytical structure. The latter course was much less entertaining, but probably far more useful for financial practitioners and students.

This book develops the foregoing themes first by laying the analytical groundwork for valuation of both nominal and inflation-adjusted cash flows. The next step is to integrate these into the corporate finance model of Merton Miller. As a practitioner, I have little use for any model unless it can prove useful with real-world data. Therefore, the book next presents case studies of several large companies, including an example in how to apply the model to corporate acquisitions and mergers. Further empirical testing is then undertaken to see whether the model is useful in predicting absolute and relative market returns prospectively.

The book finally turns to the model’s implications for explaining equity market volatility and how such volatility can be combined with the model’s return forecasts to achieve optimal portfolio rebalancing. Specifically, the model is applied to the investment profession’s analog to the astrophysicist’s famed three-body problem. Our three bodies include (1) fixed-income securities whose inflation-adjusted cash flow is known (such as TIPS), (2) fixed-income securities whose nominal cash flows are highly sensitive to inflation, and (3) equities whose cash flows are resilient with respect to inflation but uncertain due to macro- and microeconomic risk factors. The implications for portfolio rebalancing run counter to much traditional current wisdom, particularly for investors with long time horizons who are best poised for exploiting changes in the relative risk-adjusted returns of the various asset classes. As a longtime Cubs fan, I have always favored underdogs. It is therefore my hope that the model implications may give at least a fighting chance to long-horizon Generation Y as it faces the looming market pressures of my 800-pound gorilla Baby Boomer generation.

I have included much important background in several appendixes. Of particular note are the first two. Appendix A is a comprehensive treatment of traditional earnings and dividend growth topics. It is especially useful for providing background on the stubborn complexities associated with the traditional dividend growth model formulations. Appendix B is highly recommended insofar as it treats measurement implications for changes in core inflation rates, as