Models for Investors in Real World Markets, by James R. THOMPSON, Edward E. WILLIAMS, and M. Chapman FINDLAY, III, Hoboken, NJ: Wiley, 2003, ISBN 0-471-35628-X, xxi + 372 pp., $84.95.
The most common cocktail party comment that I receive, when people discover that I am a statistician, is “Well, you must be a big success in the stock market.” Unfortunately, Mister Bear came to my house, too. For me, being a modeling expert may have an impact on success for applications concerning oil exploration, refinery processes, and chemical plants and products, but that skill is not practical in the markets. The senior author of this book is a very well-known statistician and a famous modeler (see, e.g., the textbook products of his expertise in Thompson 1989 and Thompson 2000). Here he joins with a couple of investment experts to apply his modeling skills to the financial markets.
Although this book is part of the publisher’s renowned “Series in Probability and Statistics,” the book is probably focused more toward the investment community than statisticians. There are no statistics prerequisites; the book concludes with an appendix, “A Brief Introduction to Probability and Statistics” (mostly the former). The book’s mathematical content is no more advanced than differential calculus and differential equations (albeit with very heavy measures of each). After reading the Preface, I wondered if I had enough background in finance to read the book. It was quickly apparent that the book was going to bash most conventional investment wisdom, at least before the “.com” crash, on generating good returns on investments. Concerning the inimitable Alan Greenspan, “By bailing out LCTM (in 1998, a capital hedge fund) on the one hand, and stifling investment on the other, it appears he acted with the wisdom one tends to associate with the economic planning of, say, Argentina” (p. xiv). Concerning neoclassical economists, “The assumption of security progression according to a geometric Brownian walk is hugely unrealistic. Such models do not realistically admit to a large (say 5%) 24-hour change in a stock price” (p. xv). Fortunately, the first part of the book provides an excellent introduction to the world of investments. The second part proposes some appropriate modeling strategies for 21st century financial markets.
Chapter 1 presents the institutional considerations for how the markets operate, including some history about both the markets and how they have been viewed by economists. A primary theme of the book- market efficiency-is developed in this chapter. Chapter 2 describes utility theory as the basis for building investment portfolios. Chapter 3 concerns the value of diversification as a fundamental principal in making wise investment selections. Chapter 4, “Capital Market Equilibrium Theories,” and Chapter 5, “Equilibrium Implying Efficiency: The Neoclassical Fantasy,” summarize the current wisdom among financial economists (along with extensive critical commentary, of course).
Chapter 6 presents a basic valuation equation, derived more than 60 years ago, that forms the basis for the realistic approach, where probability distributions are attached to all of the underlying variables, for generating value distribution, touted in this book. Chapters 7 and 8 apply this methodology to security analysis and financial forecasting. They build a quantitative framework around financial statements. Chapter 9 presents growth as “noisy compound interest.” Chapter 10 uses risk profiles as an aid for investing in the real world to build a portfolio. Chapter 11 applies the methodology of the book to stock options. A major theme is that classical models (e.g., Keynesian economics) and much of modern computing capability, particularly simulation and resampling, can provide better guidance for investors than some of the models that won Nobel prizes for the current generation of economists.
There have been few books reported herein that I have wished so much to have had the time to read more carefully than this book. I am certainly not a knowledgeable (or, lately, successful) investor. This book is very readable and highly educational. Fortunately, statisticians are compensated adequately enough to make it relevant for all of us, It would be a good choice for your next investment.
REFERENCES
Thompson, J. (1989), Empirical Model Building, New York: Wiley.
____ (2000), Simulation: A Modeler’s Approach, New York: Wiley.
Copyright American Society for Quality Aug 2003
