Shefrin, in Behavioralizing Finance, provides a systematic analysis of how behavioral assumptions impact various aspects of modern finance theory. He posits a world in which investors begin with unequal wealth endowments, have different probability assessments of future events (some are pessimistic, some are optimistic, some are overconfident, and some are rational, with probability assessments changing over time), and have different risk preferences.
The result is a composite probability distribution of future events which differs in important respects from the true probability distribution. The differences between composite and true probabilities leads to pricing distortions. Individual securities, as well as market-wide indices, can go from being undervalued to overvalued and back again. Shefrin believes that “the future of finance will combine realistic assumptions from behavioral finance and rigorous analysis from neoclassical finance.” I hope to take a step in this direction by showing the implications of such a dynamic pricing model for how investing decisions should be made in light of emotional investors.
I must mention Robert Haugen and his book The Inefficient Stock Market. In the mid-90s as I was actively questioning the validity of MPT, I came across this excellent book which confirmed many of the things I was thinking at the time. It provided arguments and empirical results challenging the pillars of MPT. He essentially posited a behavioral market in which pricing distortions were common. He captured these distortions by means of a multi-factor proxy model based on PE ratios, growth rates, debt ratios, and other company characteristics. I used his book in my securities classes at Daniels for nearly 20 years. Haugen provided an important stepping stone on my journey to BPM, and for that I am thankful.
I would like to thank Craig Callahan, friend and colleague, for posing the initial questions and providing support for the research project which has produced one surprising result after another and is the basis for this book. Gary Black of Janus Capital saw early potential in this project and provided initial research funding. For many years I have enjoyed and benefited from my conversations with my friend and industry veteran Andrew Cox. Academic colleagues Russ Wermers, Levon Goukasian, Hersh Shefrin, Oliver Boguth, Russ Goyenko, Randy Cohen, Malcolm Baker and Gene Fama have provided useful insights over the years. Jeff Wurgler, Ken French and Jay Ritter generously provided data for testing purposes. This book would not have been possible without the support and infrastructure development provided by my colleagues at AthenaInvest: Andy Howard, Joel Coppin and Lambert Bunker.
And most importantly, the unwavering love and support of my wife Mitch has been indispensable. She has stood by me for 40 years, through the trying years of the PhD program and now through the trying years of launching a new business. To her I dedicate this book with love.
Executive Summary
In this executive summary I present the most important features and conclusions of my research, broken down by chapter so that readers can navigate to topics of interest. This Executive Summary thus acts as a more detailed contents page – helping you find your way to specific areas – and also provides a guide to the most significant conclusions that I present.
Behavioral Portfolio Management (BPM) is presented as a superior way to make investment decisions. BPM’s first basic principle is that Emotional Crowds dominate the determination of both prices and volatility, with fundamentals playing a small role. The second basic principle is that Behavioral Data Investors earn superior returns. The third basic principle is that investment risk is the chance of underperformance. (See Chapter 1.)
Emotions and heuristics dominate our decision process – they act as brakes on our investing, preventing us from making good decisions. How do we avoid falling prey to emotionally-driven and ineffective heuristics? This is a challenge since money and market volatility stir up strong emotions and so we have to constantly work to not let them control our thinking. (See Chapter 2.)
We do not have the ability to intuitively identify trends in financial time series. Thus a successful market timing approach must be based on rigorous analysis, revealing both statistical and economic significance. The identification of such a process is complicated by investor myopic loss aversion, driving us to seek relief from short-term losses, while making us susceptible in any number of poorly tested timing techniques. Achieving a DNA level understanding of randomness is a critical step to becoming a successful Behavioral Data Investor. (See Chapter 3.)
The investment industry is dominated by a Cult of Emotions in which investors make emotional decisions and the industry does little to discourage them to do otherwise. Particularly pernicious are the Cult Enforcers who use the emotional tools of MPT to keep investors from building superior portfolios. (See Chapter 4.)
The typical emotional, anecdotal investor makes poor decisions. Myopic loss aversion interacts with social validation which interacts with availability bias which interacts with mental accounting and so on, leading to the careful creation of inferior portfolios. (See Chapter 5.)
Like any good scientific, rational, truth-seeking organization, the finance profession has chosen to reject the world rather than reject the empirically discredited MPT. Now that we have spent the last 40 years, essentially my entire professional career, waiting for evidence supportive of MPT to appear and seeing none, it is time to move on. Luckily an alternative is emerging: behavioral finance. (See Chapter 6.)
Diversification, remembering the name of the stock in which you invested, and the price you paid for it, are a few of the things that lead to poor investment decisions and should be avoided. (See Chapter 7.)
The traditional mountain chart for representing investment performance is an emotionally-driven, random representation of portfolio returns. Instead, return histograms and matched returns are a more meaningful way to present what an investor can expect when making an investment. Equity return distributions are self-healing in that negative returns are more than offset by matching positive returns within the distribution. Investor patience is rewarded by this self-healing feature. (See Chapter 8.)
Among active equity mutual fund managers, style drift is part and parcel of superior performance. Without style drift, a manager cannot produce superior investment returns. The ill-conceived, leaderless stampede that is the style grid is a major contributor to active equity underperformance. The consistent pursuit of a narrowly-defined equity strategy, while taking high-conviction positions, produces both superior performance and style drift. (See Chapter 9.)
In the pantheon of investment virtues, diversification is right up there. It is so widely accepted that nary an objection is raised against it. I feel much differently and, in fact, I believe there are very few situations in which diversification makes sense. It is akin to bubble wrapping your portfolio. (See Chapter 10.)
While emotions are part and parcel of human nature, responding to gut-wrenching volatility by exiting the stock market hurts both short-term and long-term portfolio performance. At the very least, clients should stay the course in the face of rising volatility, and maybe even increase equity exposure. In short, they should avoid falling into the Volatility Trap. (See Chapter 11.)
It is important to distinguish between emotions and investment risk so that good decisions are made. Most currently used measures of risk are really measures of emotion. As it stands, finance academics have almost nothing meaningful to say about measuring true investment risk. (See Chapter 12.)
When building a successful strategy, it is necessary to identify a limited number of behavioral factors upon which to focus. Superior portfolios are created by consistently pursuing a narrowly-defined investment strategy while taking high-conviction positions. What matters in executing a strategy is not consistent returns and not a consistent set of stock characteristics such as market cap and PE, but rather the consistent pursuit of the strategy. (See Chapter 13.)
Stock picking skill is common among active equity mutual funds. Much of that skill resides among buy-side analysts with portfolio managers displaying less skill. Best and worst stocks are identified using