Return Reversals, Idiosyncratic Risk, and Expected Returns


Book Description

The empirical evidence on the cross-sectional relation between idiosyncratic risk and expected stock returns is mixed. We demonstrate that the omission of the previous month's stock returns can lead to a negatively biased estimate of the relation. The magnitude of the omitted variable bias depends on the approach to estimating the conditional idiosyncratic volatility. Although a negative relation exists when the estimate is based on daily returns, it disappears after return reversals are controlled for. Return reversals can explain both the negative relation between value-weighted portfolio returns and idiosyncratic volatility and the insignificant relation between equal-weighted portfolio returns and idiosyncratic volatility. In contrast, there is a significantly positive relation between the conditional idiosyncratic volatility estimated from monthly data and expected returns. This relation remains robust after controlling for return reversals.




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.




Idiosyncratic Risk and the Cross-Section of Expected Stock Returns


Book Description

Theories such as Merton (1987, Journal of Finance) predict a positive relation between idiosyncratic risk and expected return when investors do not diversify their portfolio. Ang, Hodrick, Xing, and Zhang (2006, Journal of Finance 61, 259-299) however find that monthly stock returns are negatively related to the one-month lagged idiosyncratic volatilities. I show that idiosyncratic volatilities are time-varying and thus their findings should not be used to imply the relation between idiosyncratic risk and expected return. Using the exponential GARCH models to estimate expected idiosyncratic volatilities, I find a significantly positive relation between the estimated conditional idiosyncratic volatilities and expected returns. Further evidence suggests that Ang et al.'s findings are largely explained by the return reversal of a subset of small stocks with high idiosyncratic volatilities.




Idiosyncratic Risk and Expected Returns


Book Description

This dissertation, "Idiosyncratic Risk and Expected Returns: an Investigation in the Context of Real Estate Investment in China" by Wei, Liu, 刘巍, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: In the asset-pricing framework, idiosyncratic risk is the risk that is independent of systematic risk and peculiar to one specific asset or company, it is left with no role in expected returns according to the classic finance theory since it could be completely diversified away. However, in the case investors holding under-diversified portfolios, previous theoretical studies generally demonstrate a positive relationship between idiosyncratic risk and expected returns. However, negative empirical evidences regarding the idiosyncratic risk-return tradeoff have been reported recently in the stock market of the U.S. and China, as well as in several real estate literatures. To reconcile the conflict, this thesis is dedicated to investigate the role of idiosyncratic risk in the context of real estate investment. In the theoretical exploration, an asset-pricing model with short-sales restrictions in the market and heterogeneous beliefs among investors is established. Specifically, a simplified version with only three risky assets, in which two of them are direct and indirect real estate investments, demonstrates when investors endowed with incomplete information setting and under-diversified holdings, idiosyncratic risk would play an important role in the expected returns in equilibrium. Furthermore, the comparative static analysis reveals a positive cross-sectional relationship between idiosyncratic risk and expected returns. In the empirical study, this thesis employs the Fama and French (1992) three-factor model to estimate monthly idiosyncratic volatilities of the Listed Property Companies (LPCs) in the A-share market of China, based on the daily data from May 1999 to Aug 2011. Specifically, for each LPC in each month, its idiosyncratic risk is computed as the standard deviation of the three-factor model's daily residuals. The estimation outputs show that idiosyncratic volatility dominates the LPCs' overall volatility during the study period, and it is features with a distinct pattern when compared to that of the U.S. REITs: the LPCs' idiosyncratic volatilities are significantly higher and more persistent; they are less irrelevant to the firm's market capitalization and present an evident co-movement with the broad market. Hence, this scenario reveals a special interest to further study on the cross-sectional relationship between the LPCs' idiosyncratic risk and their expected returns. In the cross-sectional test, conditional idiosyncratic volatility forecasted by the EGARCH-GED model is employed as the proxy for expected idiosyncratic risk, as the LPCs' lagged idiosyncratic risk is shown to be not a good estimate. Over the study period, a firm positive cross-sectional relationship between idiosyncratic risk and expected returns is documented, after controlling for various pricing factors such as firm size and book-to-market equity ratio, indicators of liquidity and momentum as well as returns reversal effect. This evidence not only confirms the prediction of previous theoretical studies and the model in this thesis, it also suggests a profitable trading strategy based on the idiosyncratic risk of the LPCs. DOI: 10.5353/th_b5108639 Subjects: Real estate investment - China Real estate investment - Rate of return




Idiosyncratic Volatility and the Cross-Section of Expected Returns


Book Description

This paper examines the cross-sectional relation between idiosyncratic volatility and expected stock returns. The results indicate that (i) data frequency used to estimate idiosyncratic volatility, (ii) weighting scheme used to compute average portfolio returns, (iii) breakpoints utilized to sort stocks into quintile portfolios, and (iv) using a screen for size, price and liquidity play a critical role in determining the existence and significance of a relation between idiosyncratic risk and the cross-section of expected returns. Portfolio-level analyses based on two different measures of idiosyncratic volatility (estimated using daily and monthly data), three weighting schemes (value-weighted, equal-weighted, inverse-volatility-weighted), three breakpoints (CRSP, NYSE, equal-market-share), and two different samples (NYSE/AMEX/NASDAQ and NYSE) indicate that there is no robust, significant relation between idiosyncratic volatility and expected returns.







The negative relationship between the cross-section of expected returns and lagged idiosyncratic volatility. The German stock market 1990-2016


Book Description

Master's Thesis from the year 2018 in the subject Business economics - Review of Business Studies, grade: 1.0, University of Hannover (Institute of Financial Markets), language: English, abstract: The main goal of this thesis is to examine whether the negative relationship between the cross-section of expected returns and lagged idiosyncratic volatility also can be found for the German stock market for the period of January 1990 through June 2016, by sorting stocks into portfolios on the basis of their idiosyncratic volatility estimates. This procedure follows Ang et al. (2006). Similar to the findings of Ang et al. (2006) for the US stock market this paper shows that there is a significant difference in returns relative to the Fama-French three-factor model, between portfolios of stocks with high and portfolios of stocks with low past idiosyncratic volatility. Although for the period 1990 - 2016 no relationship between lagged idiosyncratic volatility and the cross-section of stock returns has been found, the Idiosyncratic Volatility Puzzle reveals itself for the sub-period 2003 - 2016, when the respective portfolios of stocks with different levels of idiosyncratic volatility are controlled for size.




Stocks, Bonds, Bills, and Inflation


Book Description




Idiosyncratic Volatility and Stock Returns


Book Description

Empirical evidences regarding the association of idiosyncratic volatility and stock returns are inconsistent with the capital asset pricing model (CAPM) which implies that idiosyncratic risk should not be priced because it would be fully eliminated through diversification. Using estimated-EGARCH conditional idiosyncratic volatility of individual stocks across 36 countries from 1973 to 2007, we find that idiosyncratic risk is priced on a significantly positive risk premium for stock returns. The evidence is statistically and economically significant. It overwhelmingly supports the prediction of existing theories that idiosyncratic risk is positively related to expected returns.