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Popularity: A Bridge between Classical and Behavioral Finance

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Overview

Popularity is a word that embraces how much anything is liked, recognized, or desired. Popularity drives demand. In this book, we apply this concept to assets and securities to explain the premiums and so-called anomalies in security markets, especially the stock market.

Most assets and securities have a relatively fixed supply over the short or intermediate term. Popularity represents the demand for a security—or perhaps the set of reasons why a security is demanded to the extent that it is—and thus is an important determinant of prices for a given set of expected cash flows.

A common belief in the finance literature is that premiums in the market are payoffs for the risk of securities—that is, they are “risk” premiums. In classical finance, investors are risk averse, and market frictions are usually assumed away. In the broadest context, risk is unpopular. The largest risk premium is the equity risk premium (i.e., the extra expected return for investing in equities rather than bonds or risk-free assets). Other risk premiums include, for example, the interest rate term premium (because of the greater risk of longer-term bonds) and the default risk premium in bond markets.

There are many premiums in the market that may or may not be related to risk, but all are related to investing in something that is unpopular in some way. We consider premiums to be the result of characteristics that are systematically unpopular—that is, popularity makes the price of a security higher and the expected return lower, all other things being equal. Preferences that influence relative popularity can and do change over time. These premiums include the size premium, the value premium, the liquidity premium, the severe downside premium, low volatility and low beta premiums, ESG premiums and discounts, competitive advantage, brand, and reputation. In general, any type of security with characteristics that tend to be overlooked or unwanted can have a premium.

The title of this book refers to a bridge between classical and behavioral finance. Both approaches to finance rest on investor preferences, which we cast as popularity.

In classical finance, risk (and in particular, systematic risk) is the primary asset characteristic to which investors are averse. The CAPM says that all assets are priced according to a single, systematic factor—namely, “market risk” or covariance with the capitalization-weighted market portfolio. In contrast, we believe that risks can also be multi-dimensional, including various types of stock or bond risks. The specific structure of risk and different types of risk can also be priced, such as catastrophic risk. Although classical finance usually assumes away market frictions, rational investors may have preferences for market liquidity, favorable tax treatments, or asset divisibility, making assets more or less valuable to the extent they embody these characteristics.

In behavioral finance, investors may not be completely rational. Thus, investors may have preferences that go beyond rational behavior. We classify behavioral biases into two distinct types, psychological and cognitive. Psychological desires cause some assets to be more popular than others, relative to their expected cash flow and relative to other rational characteristics, such as liquidity. Investors’ rationality is also limited because they make cognitive errors.

Neoclassical economics provides the rationality framework for efficient capital markets. Behavioral economics assumes limited or “bounded” rationality and thus provides the framework for prospect theory, loss aversion, framing, mental accounting, overconfidence, and other inconsistencies with rational behavior. Popularity represents all of our preferences, which can be rational or irrational, providing a bridge between classical and behavioral finance.

The CAPM is an elegant and easy-to-use theory for describing investor expected returns in an equilibrium setting. It assumes that investors are rational and risk averse. Because they can diversify away from all non-market risk, only systematic market risk in securities is priced. Securities with higher systematic risk have lower relative prices and thus higher expected returns. We introduce a new formal asset pricing model, the popularity asset pricing model (PAPM), that extends the CAPM to include all types of preferences.

The PAPM is an outgrowth of New Equilibrium Theory (NET), a framework proposed by Ibbotson, Diermeier, and Siegel (Financial Analysts Journal 1984) in which investors are rational but have preferences for or aversions to various security characteristics beyond the single market risk of the CAPM. Additionally, NET goes beyond the multiple dimensions of risk that might be modeled in the arbitrage pricing theory (APT). In NET, in addition to systematic risk aversion, investors have a rational aversion to assets that are difficult to diversify, are less liquid, are highly taxed, or are not easily divisible. All of these preferences impact the prices and expected returns of assets that embody these characteristics.

The PAPM goes even further, providing a theory in an equilibrium framework by including both risk aversion and popularity preferences on the part of the investors. These preferences can be rational, as in NET, or irrational, as in behavioral economics. In the PAPM, securities have a variety of characteristics or dimensions of popularity: different systematic or unsystematic risks and a variety of additional attributes that some or all investors care about. All of these characteristics are priced according to the aggregate demand for each of the characteristics. The expected return of each security is determined by its risk and other popularity characteristics.

The concept of a negative return to popularity (which we shorten to just “popularity”) has been shown to be consistent with the empirical premiums found in the stock market. But it is an explanation after the fact. More direct tests involve identifying in advance what characteristics are likely to be popular and then comparing the performance of stocks that should be unpopular with that of stocks that should be popular based on those characteristics.

We did this for five characteristics. First, we argue that companies with high brand values are popular. These companies end up having significantly lower returns than those with the lowest brand value over our period of study. Second, we argue that companies with wide economic moats, having a sustainable competitive advantage, are more popular. We found that companies with no moat outperform the wide moat companies. Third, we found that companies with a better reputation tend to underperform companies with a worse one. Fourth, we argue that stocks that have had historical negative tail risk events (low or negative coskewness) are unpopular. We found that these stocks significantly outperformed those with high coskewness over the period of study. Finally, we argue that stocks with positive historical skewness are popular because they provide the apparent opportunity for outsized gains. We found that these stocks have the lowest risk-adjusted returns over our period of study.

When we did our five direct tests of the popularity hypothesis, we looked at both equally-weighted composites and market capitalization-weighted composites of the stocks, giving us 10 tests. While all results, to a moderate or high degree, were consistent with the popularity hypothesis, only 5 out of 10 were consistent with the “more risk equals more return” paradigm.

We also tested most of the well-known premiums and anomalies for consistency with popularity. We found that low-beta, low-volatility, small-cap, value, and less liquid stocks, being less popular, outperformed their more popular counterparts. To do this, we looked at 10 of the factor tests in Ibbotson and Kim (working paper 2017) through the popularity lens. Of the 10 different factors that we looked at, we found that 7 were consistent with the popularity hypothesis while only 2 were consistent with the “more risk equals more return” paradigm. We also found that within the stock market, the portfolios formed based on these characteristics had an inverse relationship between risk and return, counter to classical theory. Either risk is popular under some circumstances, or other non-risk characteristics dominate returns. We believe that popularity reflects the demand that ultimately determines prices and returns. 

The numerous empirical flaws of the CAPM, and the notion that more risk should equate to more return, have given rise to a variety of behavioral based explanations for observed asset prices. Popularity in general, and the PAPM in particular, unifies the driving factors that impact price in the classical finance CAPM world with those that drive price in a behavioral asset pricing world. In this way, popularity creates a unifying theory—a bridge between classical and behavioral finance.

 

Contents

Foreword  ix
    Laurence B. Siegel
    The Classical Answer  ix
    The Behavioral Answer  x
    Reducing the Complexity of the Market  x
    How Popularity and Other Factors Set Prices  xi
    From New Equilibrium Theory to the Popularity Asset Pricing Model  xi
    Understanding Historical Returns  xii
    A New Kind of Forecasting  xii
    The Supply of Capital Market Returns  xiii
    The Liquidity Factor  xiv
    Conclusion: It’s Hard but Not Impossible to Beat the Market  xv
Preface  xvii

1. Introduction  1
    What Is Popularity?  1
    Principles and Models of Classical Finance  4
    Principles of Behavioral Finance  6
    Demand and Supply  7
    Popularity Premiums  9
    Premiums vs. Mispricing  11
    Popularity and Adaptive Markets  12
2. Premiums, Anomalies, and Popularity  14
    Asset Class Risks  15
    The Equity Premium  17
    Premiums and Anomalies within Equity Markets  18
    Conclusion  27
    Appendix A. Psychic Returns in Art Markets  28
    Conclusion  30
3. Popularity and Asset Pricing  31
    Refining the Popularity Framework  32
    Precursors to the Popularity Approach  33
    Efficient Markets, Behavioral Finance, or Something Else?  34
    A Popularity-Based Asset Pricing Formula  37
    Conclusion  42
4. New Equilibrium Theory  43
    The Central Ideas of NET  43
    A Formal Model for NET  45
    Issues That the NET Framework Can Address  47
    Asset Class Characteristics  52
    Conclusion  52
5. The Popularity Asset Pricing Model  55
    Review of the CAPM  57
    The Popularity Asset Pricing Model  62
    A Numerical Example  67
    Conclusion  72
    Appendix B. Formal Presentation of the CAPM  73
    Appendix C. Formal Presentation of the PAPM  79
6. New Empirical Evidence for Popularity  84
    Popular Company Characteristics  84
    Tail Risk (Coskewness)  101
    Lottery Stocks  104
    Conclusion  107
7. Empirical Evidence of Popularity from Factors  112
    Returns and Factors  112
    Beta and Volatility  115
    Size  118
    Value  119
    Liquidity  122
    Momentum  122
    Conclusion  126
8. Summary and Conclusions  127
    Popularity as a Concept  127
    Popularity as a Bridge between Classical and Behavioral Finance  128
    Popularity as a Theory  129
    Empirical Evidence for Popularity  130
    References  132

 
 

About the Author(s)

Roger Ibbotson
Roger G. Ibbotson

Roger G. Ibbotson is Professor in the Practice Emeritus of Finance at Yale School of Management and chairman of Zebra Capital Management, LLC, a global equity investment and hedge fund manager. He is founder and former chairman of Ibbotson Associates. Professor Ibbotson conducts research on a broad range of financial topics, including popularity, liquidity, investment returns, mutual funds, international markets, portfolio management, and valuation. He has written numerous books and articles, including Stocks, Bonds, Bills, and Inflation (coauthored by Rex Sinquefield), which is updated annually and serves as a standard reference for information and capital market returns. Professor Ibbotson’s other books include The Equity Risk Premium, Lifetime Financial Advice, and, most recently, Popularity: A Bridge between Classical and Behavioral Finance. He is a regular contributor to and an editorial board member of both trade and academic journals. Professor Ibbotson serves on numerous boards and frequently speaks at universities, conferences, and other forums. He received his bachelor’s degree in mathematics from Purdue University, his MBA from Indiana University, and his PhD from the University of Chicago, where he also taught for more than 10 years and served as executive director of the Center for Research in Security Prices.

Thomas Idzorek
Thomas M Idzorek CFA

Thomas M. Idzorek, CFA, is chief investment officer, retirement, for Morningstar Investment Management LLC. He also serves as a member of Morningstar’s 401(k) committee and Public Policy Council, chair of Morningstar’s overall Research Council, and as a member on the editorial boards of the CFA Institute Financial Analysts Journal and Morningstar magazine. Idzorek was formerly president of Morningstar’s global investment management division, where he oversaw the firm’s global investment advice, consulting, retirement solutions, broker/dealer, index, and financial wellness businesses. Additionally, he has served as president of Ibbotson Associates, president of Morningstar Associates, board member/responsible officer for a number of Morningstar Investment Management subsidiaries, global chief investment officer for Morningstar Investment Management, chief investment officer for Ibbotson Associates, and director of research and product development for Ibbotson. Most recently, Idzorek served as head of investment methodology and economic research for Morningstar. Before joining Ibbotson, he was a senior quantitative researcher for Zephyr Associates. Idzorek has written numerous articles for academic and industry journals and collaborated on papers that have won a Financial Analysts Journal Graham & Dodd Scroll Award. He is an expert on multiasset class strategic asset allocation, the Black–Litterman model, target date funds, retirement income solutions, fund-of-funds optimization, risk budgeting, and performance analysis. Idzorek is the key methodological creator of Morningstar’s target date and retirement managed account (robo-advice) solution. He holds a bachelor’s degree in marketing from Arizona State University and a master’s degree in business administration from Thunderbird School of Global Management.

Paul Kaplan
Paul D. Kaplan CFA

Paul D. Kaplan, CFA, is director of research for Morningstar Canada and is a senior member of Morningstar’s global research team. He led the development of many of the quantitative methodologies behind Morningstar’s fund analysis, indexes, adviser tools, and other services. Kaplan conducts research on asset allocation, retirement income planning, portfolio construction, index methodologies, and other investment topics. Many of his research papers have been published in professional books and publications, such as the Financial Analysts Journal and the Journal of Portfolio Management, and he has served on the editorial board of the Financial Analysts Journal. Kaplan has received a Graham & Dodd Top Award and a Graham & Dodd Award of Excellence. Many of his works appear in his book Frontiers of Modern Asset Allocation. Previously, he has served as quantitative research director for Morningstar Europe in London, director of quantitative research in the United States, and chief investment officer of Morningstar Associates, LLC, where he developed and managed the investment methodology for Morningstar’s retirement planning and advice services. Previously, Kaplan was a vice president of Ibbotson Associates and served as the firm’s chief economist and director of research. Prior to that, he served on the economics faculty of Northwestern University, where he taught international finance and statistics. Kaplan holds a bachelor’s degree in mathematics, economics, and computer science from New York University and a master’s degree and doctorate in economics from Northwestern University.

James Xiong
James X. Xiong CFA

James X. Xiong, CFA, is head of scientific investment management research at Morningstar Investment Management. He leads research and develops new methodologies and algorithms on the time-varying capital markets model, tail risk management, portfolio optimization, asset allocation, dynamic portfolio choice, insurance product allocation, mutual fund selection, alternative asset class investments, Monte Carlo simulations, and other investment and financial planning areas. Xiong’s work has been published in the Financial Analysts Journal, Journal of Investment Management, Journal of Portfolio Management, Journal of Risk Management in Financial Institutions, and Journal of Financial Planning, among other publications. His co-authored “Liquidity Style of Mutual Funds” was awarded with a Graham & Dodd Scroll, and his co-authored “Momentum, Acceleration and Reversal” won a Harry M. Markowitz Award. Xiong has published more than 15 papers in scientific journals, including Physical Review Letters, a prestigious world journal in physics. He holds a bachelor’s degree in physics from Wuhan University in China and a doctorate in physics from the University of Houston.

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Book Information

Published by CFA Institute Research Foundation

140 pages

ISBN: 978-1-944960-60-5

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