Since the formalization of asset allocation in 1952 with the publication of Portfolio Selection by Harry Markowitz, academics and practitioners alike have made great strides to enhance the application of this groundbreaking theory. However, as in many circumstances of scientific development, progress has been uneven. It has been punctuated with instances of misleading research, which has contributed to the stubborn persistence of certain fallacies about asset allocation. Our goal in writing this book is twofold: to describe several important innovations that address key challenges to asset allocation and to dispel certain fallacies about asset allocation.
We divide the book into four sections. Section I covers the fundamentals of asset allocation, including a discussion of the attributes that qualify a group of securities as an asset class, as well as a detailed description of the conventional application of mean‐variance analysis to asset allocation. In describing the conventional approach to asset allocation, we include an illustrative example that serves as a base case, which we use to demonstrate the impact of the innovations we describe in subsequent chapters.
Section II presents certain fallacies about asset allocation, which we attempt to dispel either by logic or with evidence. These fallacies include the notion that asset allocation determines more than 90 percent of investment performance, that time diversifies risk, that optimization is hypersensitive to estimation error, that factors provide greater diversification than assets and are more effective at reducing noise, and that equally weighted portfolios perform more reliably out of sample than optimized portfolios.
Section III describes several innovations that address key challenges to asset allocation. We present an alternative optimization procedure to address the challenge that some investors have complex preferences and returns may not be elliptically distributed. We show how to overcome inefficiencies that result from constraints by augmenting the optimization objective function to incorporate absolute and relative goals simultaneously. We address the challenge of currency risk by presenting a cost/benefit analysis of several linear and nonlinear currency‐hedging strategies. We describe how to use shadow assets and liabilities to unify liquidity with expected return and risk. We show how to evaluate alternative asset mixes by assessing exposure to loss throughout the investment horizon based on regime‐dependent risk. We address estimation error in covariances by introducing a nonparametric procedure for incorporating the relative stability of covariances directly into the asset allocation process. We address the challenge of choosing between leverage and concentration to raise expected return by relaxing the simplifying assumptions that support the theoretical arguments. We describe a dynamic programming algorithm as well as a quadratic heuristic to determine a portfolio's optimal rebalancing schedule. Finally, we address the challenge of regime shifts with several innovations, including stability‐adjusted optimization, blended covariances, and regime indicators.
Section IV provides supplementary material. For readers who have more entertaining ways to spend their time than reading this book, we summarize the key takeaways in just a few pages. We also provide a chapter on relevant statistical and theoretical concepts, and we include a comprehensive glossary of terms.
This book is not an all‐inclusive treatment of asset allocation. There are certainly some innovations that are not known to us, and there are other topics that we do not cover because they are well described elsewhere. The topics that we choose to write about are ones that we believe to be especially important, yet not well known nor understood. We hope that readers will benefit from our efforts to convey this material, and we sincerely welcome feedback, be it favorable or not.
Some of the content of this book originally appeared as journal articles that we coauthored with past and current colleagues. We would like to acknowledge the contributions of Wei Chen, George Chow, David Chua, Paula Cocoma, Megan Czasonis, Eric Jacquier, Kenneth Lowry, Simon Myrgren, Sébastien Page, and Don Rich.
In addition, we have benefited enormously from the wisdom and valuable guidance, both directly and indirectly, from a host of friends and scholars, including Peter Bernstein, Stephen Brown, John Campbell, Edwin Elton, Frank Fabozzi, Gifford Fong, Martin Gruber, Martin Leibowitz, Andrew Lo, Harry Markowitz, Robert C. Merton, Krishna Ramaswamy, Stephen Ross, Paul A. Samuelson, William Sharpe, and Jack Treynor. Obviously, we accept sole responsibility for any errors.
Finally, we would like to thank our wives, Michelle Kinlaw, Abigail Turkington, and Elizabeth Gorman, for their support of this project as well as their support in more important ways.