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  Investors and Markets  Portfolio Choices, Asset Prices, and Investment Advice  
 By William F. Sharpe   Princeton University Press  
Copyright © 2006   Princeton University 
All right reserved. ISBN: 978-0-691-13850-3 
    Chapter One   INTRODUCTION    1.1. The Subject of This Book  
  
  THIS IS A BOOK about the effects of investors interacting in capital  markets and the implications for those who advise individuals concerning  savings and investment decisions. The subjects are often considered  separately under titles such as portfolio choice and asset pricing.  
  Portfolio choice refers to the ways in which investors do or should make  decisions concerning savings and investments. Applications that are  intended to describe what investors do are examples of positive economics.  Far more common, however, are normative applications, designed to  prescribe what investors should do.  
  Asset pricing refers to the process by which the prices of financial  assets are determined and the resulting relationships between expected  returns and the risks associated with those returns in capital markets.  Asset pricing theories or models are examples of positive or descriptive  economics, since they attempt to describe relationships in the real world.  In this book we take the view that these subjects cannot be adequately  understood in isolation, for they are inextricably intertwined. As will be  shown, asset prices are determined as part of the process through which  investors make portfolio choices.Moreover, the appropriate portfolio  choice for an individual depends crucially on available expected returns  and risks associated with different investment strategies, and these  depend on the manner in which asset prices are set. Our goal is to  approach these issues more as one subject than as two. Accordingly, the  book is intended for those who are interested in descriptions of the  opportunities available in capital markets, those who make savings and  investment decisions for themselves, and those who provide such services  or advice to others.  
  Academic researchers will find here a series of analyses of capital market  conditions that go well beyond simple models that imply portfolio choices  clearly inconsistent with observed behavior. A major focus throughout is  on the effects on asset pricing when more realistic assumptions are made  concerning investors' situations and behavior.  
  Investment advisors and investment managers will find a set of possible  frameworks for making logical decisions, whether or not they believe that  asset prices well reflect future prospects. It is crucial that investment  professionals differentiate between investing and betting. We show that a  well thought out model of asset pricing is an essential ingredient for  sound investment practice. Without one, it is impossible to even know the  extent and nature of bets incorporated in investment advice or management,  let alone ensure that they are well founded.  
  
  1.2. Methods  
  This book departs from much of the previous literature in the area in two  important ways. First, the underlying view of the uncertain future is not  based on the mean/variance approach advocated for portfolio choice by  Markowitz (1952) and used as the basis for the original Capital Asset  Pricing Model (CAPM) of Sharpe (1964), Lintner (1965), Mossin (1966), and  Treynor (1999). Instead, we base our analyses on a straightforward version  of the state/preference approach to uncertainty developed by Arrow (1953)  extending the work of Arrow (1951) and Debreu (1951).  
  Second, we rely extensively on the use of a program that simulates the  process by which equilibrium can be reached in a capital market and  provides extensive analysis of the resulting relationships between asset  prices and future prospects.  
  
  1.2.1. The State/Preference Approach  
  We utilize a state/preference approach with a discrete-time,  discrete-outcome setting. Simply put, uncertainty is captured by assigning  probabilities to alternative future scenarios or states of the world, each  of which provides a different set of investment outcomes. This rules out  explicit reliance on continuous-time formulations and continuous  distributions (such as normal or log-normal), although one can use  discrete approximations of such distributions.  
  Discrete formulations make the mathematics much simpler. Many standard  results in financial economics can be obtained almost trivially in such a  setting. At least as important, discrete formulations can make the  underlying economics of a situation more obvious. At the end of the day,  the goal of the (social) science of financial economics is to describe the  results obtained when individuals interact with one another. The goal of  financial economics as a prescriptive tool is to help individuals make  better decisions. In each case, the better we understand the economics of  an analysis, the better equipped we are to evaluate its usefulness. The  term state/preference indicates both that discrete states and times are  involved, and that individuals' preferences for consumption play a key  role. Also included are other aspects, such as securities representing  production outputs.  
  
  1.2.2. Simulation  
  Simulation makes it possible to substitute computation for derivation.  Instead of formulating complex algebraic models, then manipulating the  resulting equations to obtain a closed-form solution equation, one can  build a computer model of a marketplace populated by individuals, have  them trade with one another until they do not wish to trade any more, then  examine the characteristics of the resulting portfolios and asset prices.  
  Simulations of this type have both advantages and disadvantages. They can  be relatively easy to understand. They can also reflect more complex  situations than must often be assumed if algebraic models are to be used.  On the other hand, the relationship between the inputs and the outputs may  be difficult to fully comprehend. Worse yet, it is hard if not impossible  to prove a relationship via simulation, although it is possible to  disprove one.  
  Consider, for example, an assertion that when people have preferences of  type A and securities of type B are available, equilibrium asset prices  have characteristics of type C; that is, A + B  C. One can run a  simulation with some people of type A and securities of type B and observe  that the equilibrium asset prices are of type C. But this does not prove  that such will always be the case. One can repeat the experiment with  different people and securities, but always with people of type A and  securities of type B. If in one or more cases the equilibrium is not of  type C, the proposition (A + B  C) is disproven. But even if every  simulation conforms with the proposition, it is not proven. The best that  can be said is that if many simulations give the same result, one's  confidence in the truth of the proposition is increased. Simulation is  thus at best a brute force way to derive propositions that may hold most  or all of the time.  
  But equilibrium simulation can be a powerful device. It can produce  examples of considerable complexity and help people think deeply about the  determinants of asset prices and portfolio choice. It can also be a  powerful ally in bringing asset pricing analysis to more people.  
  
  1.2.3. The APSIM Program  
  The simulation program used for all the examples in this book is called  APSIM, which stands for Asset Pricing and Portfolio Choice Simulator. It  is available without charge at the author's Web site: www.wsharpe.com,  along with workbooks for each of the cases covered. The program,  associated workbooks, instructions, and source code can all be downloaded.  Although the author has made every attempt to create a fast and reliable  simulation program, no warranty can be given that the program is without  error.  
  Although reading C++ programming code for a complex program is not  recommended for most readers, the APSIM source code does provide  documentation for the results described here. In a simulation context,  this can serve a function similar to that of formal proofs of results obtained with traditional algebraic models.  
  
  1.3. Pedagogy  
  If you were to attend an MBA finance class at a modern university you  would learn about subjects such as portfolio optimization, asset  allocation analysis, the Capital Asset Pricing Model, risk-adjusted  performance analysis, alpha and beta values, Sharpe Ratios, and index  funds. All this material was built from Harry Markowitz's view that an  investor should focus on the expected return and risk of his or her  overall portfolio and from the original Capital Asset Pricing Model that  assumed that investors followed Markowitz's advice. Such mean/variance  analysis provides the foundation for many of the quantitative methods used  by those who manage investment portfolios or assist individuals with  savings and investment decisions. If you were to attend a Ph.D. finance  class at the same university you would learn about no-arbitrage pricing,  state claim prices, complete markets, spanning, asset pricing kernels,  stochastic discount factors, and risk-neutral probabilities. All these  subjects build on the view developed by Kenneth Arrow that an investor  should consider alternative outcomes and the amount of consumption  obtained in each possible situation. Techniques based on this type of  analysis are used frequently by financial engineers, but far less often by  investment managers and financial advisors.  
  Much of the author's published work is in the first category, starting  with "Capital Asset Prices: A Theory of Market Equilibrium under  Conditions of Risk" (1964). The monograph Portfolio Theory and Capital  Markets (1970) followed resolutely in the mean/variance tradition,  although it did cover a few ideas from state/preference theory in one  chapter. The textbook Investments (Sharpe 1978) was predominantly in the  mean/variance tradition, although it did use some aspects of a  state/preference approach when discussing option valuation. The most  recent edition (Sharpe, Alexander, and Bailey 1999) has evolved  significantly, but still rests on a mean/variance foundation.  
  This is not an entirely happy state of affairs. There are strong arguments  for viewing mean/variance analysis as a special case of a more general  asset pricing theory (albeit a special case with many practical  advantages). This suggests that it could be preferable to teach MBA  students, investment managers, and financial advisors both general asset  pricing and the special case of mean/ variance analysis. A major goal of  this book is to show how this might be accomplished. It is thus addressed  in part to those who could undertake such a task (teachers, broadly  construed). It is also addressed to those who would like to understand  more of the material now taught in the Ph.D. classroom but who lack some  of the background to do so easily (students, broadly construed).  
  
  1.4. Peeling the Onion  
  Capital markets are complex. We deal with stylized versions that lack many  important features such as taxes, transactions costs, and so on. This is  equivalent to introducing some of the principles of physics by assuming  away the influences of friction. The justification is that one cannot hope  to understand real capital markets without considering their behavior in  simpler settings.  
  While our simulated capital markets are far simpler than real ones, their  features are not simple to fully understand. To deal with this we  introduce material in a sequential manner, starting with key aspects of a  very simple case, while glossing over many important ingredients. Then we  slowly peel back layers of the onion, revealing more of the inner workings  and moving to more complex cases. This approach can lead to a certain  amount of frustration on the part of both author and reader. But in due  course, most mysteries are resolved, seemingly unrelated paths converge,  and the patient reader is rewarded.  
  
  1.5. References  
  The material in this book builds on the work of many authors. Although  some key works are referenced, most are not because of the enormity of the  task. Fortunately, there is an excellent source for those interested in  the history of the ideas that form the basis for much of this book: Mark  Rubinstein's A History of the Theory of Investments: My Annotated  Bibliography (Rubinstein 2006), which is highly recommended for anyone  seriously interested in investment theory.  
  
  1.6. Chapters  
  A brief description of the contents of the remaining chapters follows.  
  
  1.6.1. Chapter 2: Equilibrium  
  Chapter 2 presents the fundamental ideas of asset pricing in a one-period  (twodate) equilibrium setting in which investors agree on the  probabilities of alternative future states of the world. The major focus  is on the advice often given by financial economists to their friends and  relatives: avoid non-market risk and take on a desired amount of market  risk to obtain higher expected return. We show that under the conditions  in the chapter, this is consistent with equilibrium portfolio choice.  
  
  1.6.2. Chapter 3: Preferences  
  Chapter 3 deals with investors' preferences. We cover alternative ways in  which an individual may determine the amount of a security to be purchased  or sold, given its price. A key ingredient is the concept of marginal  utility. There are direct relationships between investors' marginal  utilities and their portfolio choices. We cover cases that are consistent  with some traditional financial planning advice, others that are  consistent with mean/variance analysis, and yet others that are consistent  with some features of the experimental results obtained by cognitive  psychologists.  
  
  1.6.3. Chapter 4: Prices  
  Chapter 4 analyzes the characteristics of equilibrium in a world in which  investors agree on the probabilities of future states of the world, do not  have sources of consumption outside the financial markets, and do not  favor a given amount of consumption in one future state of the world over  the same amount in another future state. The chapter also introduces the  concept of a complete market, in which investors can trade atomistic  securities termed state claims. Some of the key results of modern asset  pricing theory are discussed, along with their preconditions and  limitations. Implications for investors' portfolio choices are also  explored. We show that in this setting the standard counsel that an  investor should avoid non-market risk and take on an appropriate amount of  market risk to obtain higher expected return is likely to be good advice  as long as available securities offer sufficient diversity.  
  
  1.6.4. Chapter 5: Positions  
 Chapter 5 explores the characteristics of equilibrium and optimal  portfolio choice when investors have diverse economic positions outside  the financial markets or differ in their preferences for consumption in  different possible states of the world. As in earlier chapters, we assume  investors agree on the probabilities of alternative future outcomes.  
  
  1.6.5. Chapter 6: Predictions  
  Chapter 6 confronts situations in which people disagree about the  likelihood of different future outcomes. Active and passive approaches to  investment management are discussed. The arguments for index funds are  reviewed, along with one of the earliest published examples of a case in  which the average opinion of a number of people provided a better estimate  of a future outcome than the opinion of all but a few. We also explore the  impact of differential information across investors and the effects of  both biased and unbiased predictions.  
  
  1.6.6. Chapter 7: Protection  
  Chapter 7 begins with a discussion of the type of investment product that  offers "downside protection" and "upside potential." Such a "protected  investment product" is a derivative security because its return is based  on the performance of a specified underlying asset or index. We show that  a protected investment product based on a broad market index can play a  useful role in a market in which some or all investors' preferences have  some of the characteristics found in behavioral studies. We also discuss  the role that can be played in such a setting by other derivative  securities such as put and call options. To illustrate division of  investment returns we introduce a simple trust fund that issues securities  with different payoff patterns. Finally, we discuss the results from an  experiment designed to elicit information about the marginal utilities of  real people.  
  (Continues...)  
     
 
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