Dispersion of Beliefs, Ambiguity, and the Cross-Section of Stock Returns


Book Description

We examine whether ambiguity is priced in the cross-section of expected stock returns. Using the cross-sectional dispersion in real-time forecasts of real GDP growth as a measure for ambiguity, we find that high ambiguity beta stocks earn lower future returns relative to low ambiguity beta stocks. This negative predictive relation between the ambiguity beta and future returns is consistent with theory, which predicts the marginal utility of consumption to rise when ambiguity is high. We further show that the ambiguity premium remains significant after controlling for exposures to expected real GDP growth, VIX, and financial market dislocations index.




Skewness and Dispersion of Opinion and the Cross Section of Stock Returns


Book Description

We show that the degree of dispersion and asymmetry of analysts' earnings forecasts is related to future stock returns. When skewness is negative, future returns are decreasing in the degree of dispersion of analysts' earnings forecasts; when skewness is positive, future returns are increasing in the degree of dispersion of analysts earnings forecasts. We develop a model that incorporates dispersion and asymmetry in agents' beliefs that can account for these empirical facts.




Differences of Opinion and the Cross-Section of Stock Returns


Book Description

We provide evidence that stocks with higher dispersion in analysts' earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks, and stocks that have performed poorly over the past year. Interpreting dispersion in analysts' forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will reflect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts' forecasts proxies for risk.




Heterogeneous Beliefs and Momentum Profits


Book Description

Recent theoretical models derive return continuation in a setting where investors have heterogeneous beliefs or receive heterogeneous information. This paper tests the link between heterogeneity of beliefs and return continuation in the cross-section of US stock returns. Heterogeneity of beliefs about a firm's fundamentals is measured by the dispersion in analyst forecasts of earnings. The results show that momentum profits are significantly larger for portfolios characterized by higher heterogeneity of beliefs. Predictive cross-sectional regressions show that heterogeneity of beliefs has a positive incremental effect on return continuation after controlling for variables measuring a stock's visibility, the speed of information diffusion, uncertainty about fundamentals, information precision, and volatility. The results in this paper are robust to the potential presence of short-sale constraints and are not explained by arbitrage risk.




Disagreement, Excess Volatility and Comovement in Stock Returns


Book Description

This paper analyzes the impact of dispersion and correlation in investors' beliefs on the cross-section of volatilities and correlations in stock returns. Theoretically, we show that, in a baseline model with logarithmic agents and constant beliefs, there is a positive relationship between belief dispersion and stock volatility, and a positive relationship between belief correlation and return correlation. Extensions to CRRA preference, learning, and multiple agents show that the baseline results are generally robust for reasonable model parameter values. Empirically, we find supporting evidence on the theoretical predictions of the baseline model using analysts' forecasts of earnings as a proxy for investors' beliefs, suggesting that disagreement provides a plausible explanation to the excess volatility and comovement in stock returns.




The Cross-sectional Dispersion of Stock Returns, Alpha and the Information Ratio


Book Description

We find that the cross-sectional dispersion of U.S. stock returns provides economically significant forecasts of alpha dispersion across high- and low-performing portfolios of stocks over 3-month and 1-year horizons. Conventional measures of time-series volatility provide similar signals regarding alpha dispersion, but neither cross-sectional return dispersion nor time-series volatility identify future dispersion in the information ratio. These results suggest that absolute return investors can use both cross-sectional dispersion and time-series volatility as signals to improve the tactical timing of their alpha-focused strategies, but relative return investors, keeping score in an information ratio framework, are unlikely to find dispersion or volatility valuable as signals of when to increase or decrease the activeness of their strategies.




Empirical Asset Pricing


Book Description

“Bali, Engle, and Murray have produced a highly accessible introduction to the techniques and evidence of modern empirical asset pricing. This book should be read and absorbed by every serious student of the field, academic and professional.” Eugene Fama, Robert R. McCormick Distinguished Service Professor of Finance, University of Chicago and 2013 Nobel Laureate in Economic Sciences “The empirical analysis of the cross-section of stock returns is a monumental achievement of half a century of finance research. Both the established facts and the methods used to discover them have subtle complexities that can mislead casual observers and novice researchers. Bali, Engle, and Murray’s clear and careful guide to these issues provides a firm foundation for future discoveries.” John Campbell, Morton L. and Carole S. Olshan Professor of Economics, Harvard University “Bali, Engle, and Murray provide clear and accessible descriptions of many of the most important empirical techniques and results in asset pricing.” Kenneth R. French, Roth Family Distinguished Professor of Finance, Tuck School of Business, Dartmouth College “This exciting new book presents a thorough review of what we know about the cross-section of stock returns. Given its comprehensive nature, systematic approach, and easy-to-understand language, the book is a valuable resource for any introductory PhD class in empirical asset pricing.” Lubos Pastor, Charles P. McQuaid Professor of Finance, University of Chicago Empirical Asset Pricing: The Cross Section of Stock Returns is a comprehensive overview of the most important findings of empirical asset pricing research. The book begins with thorough expositions of the most prevalent econometric techniques with in-depth discussions of the implementation and interpretation of results illustrated through detailed examples. The second half of the book applies these techniques to demonstrate the most salient patterns observed in stock returns. The phenomena documented form the basis for a range of investment strategies as well as the foundations of contemporary empirical asset pricing research. Empirical Asset Pricing: The Cross Section of Stock Returns also includes: Discussions on the driving forces behind the patterns observed in the stock market An extensive set of results that serve as a reference for practitioners and academics alike Numerous references to both contemporary and foundational research articles Empirical Asset Pricing: The Cross Section of Stock Returns is an ideal textbook for graduate-level courses in asset pricing and portfolio management. The book is also an indispensable reference for researchers and practitioners in finance and economics. Turan G. Bali, PhD, is the Robert Parker Chair Professor of Finance in the McDonough School of Business at Georgetown University. The recipient of the 2014 Jack Treynor prize, he is the coauthor of Mathematical Methods for Finance: Tools for Asset and Risk Management, also published by Wiley. Robert F. Engle, PhD, is the Michael Armellino Professor of Finance in the Stern School of Business at New York University. He is the 2003 Nobel Laureate in Economic Sciences, Director of the New York University Stern Volatility Institute, and co-founding President of the Society for Financial Econometrics. Scott Murray, PhD, is an Assistant Professor in the Department of Finance in the J. Mack Robinson College of Business at Georgia State University. He is the recipient of the 2014 Jack Treynor prize.




Ambiguity in the Cross-Section of Expected Returns


Book Description

This paper estimates and tests the smooth ambiguity model of Klibanoff, Marinacci, and Mukerji (2005, 2009) based on stock market data. We introduce a novel methodology to estimate the conditional expectation which characterizes the impact of a decision maker's ambiguity attitude on asset prices. Our point estimates of the ambiguity parameter are between 25 and 40, whereas our risk aversion estimates are considerably lower. The substantial difference indicates that market participants are ambiguity averse. Furthermore, we evaluate if ambiguity aversion helps explaining the cross-section of expected returns. Compared with Epstein and Zin (1989) preferences, we find that incorporating ambiguity into the decision model improves the fit to the data while keeping relative risk aversion at more reasonable levels.




Handbook of the Equity Risk Premium


Book Description

Edited by Rajnish Mehra, this volume focuses on the equity risk premium puzzle, a term coined by Mehra and Prescott in 1985 which encompasses a number of empirical regularities in the prices of capital assets that are at odds with the predictions of standard economic theory.




Robustness


Book Description

The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.