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Author: Wei Huang Publisher: ISBN: Category : Languages : en Pages : 37
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.
Author: Wei Huang Publisher: ISBN: Category : Languages : en Pages : 37
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.
Author: Xiafei Li Publisher: ISBN: Category : Languages : en Pages : 34
Book Description
This paper examines whether the negative relation between idiosyncratic volatility and expected returns is due to stock return reversals as argued by Fu (2009) and Huang, Liu, Rhee and Zhang (2010). Controlling the return reversal effect, it shows that stocks with different past returns have different relations. The positive relation is mainly driven by stocks with low past returns, while the negative relation is result from stocks with high past returns. Additionally, the relation is very sensitive to the measurement frequency of idiosyncratic volatility, and the daily realized idiosyncratic volatility measure is a better proxy for the expected idiosyncratic volatility than the monthly measure. By employing an exponential generalized autoregressive conditional heteroskedascticity-in-mean (EGARCH-M) model, this paper finds a strong positive relation between time-varying risk premium and idiosyncratic volatility for portfolios containing stocks with low past returns and small portfolio, and a negative relation for growth portfolio.
Author: Wei Huang Publisher: ISBN: Category : Languages : en Pages : 48
Book Description
We conduct comprehensive analyses of the return characteristics of stock portfolios sorted by idiosyncratic volatility. We show that the relationship between idiosyncratic volatility and expected stock returns depends on whether the portfolio is composed of stocks with extreme performance and whether the returns are computed over January and non-January months. The dominance of loser stocks in December and a reversal effect in the subsequent month lead to a positive relation between idiosyncratic volatility and portfolio returns in January. Whereas for other months, the impact of past winner stocks dominates and a negative relation is observed due to the return reversal of these winner stocks. Our study contributes to the understanding of how January effect and short-term return reversal can lead to different relation between idiosyncratic volatility and expected returns.
Author: Fangjian Fu Publisher: ISBN: Category : Languages : en Pages : 45
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.
Author: Turan G. Bali Publisher: John Wiley & Sons ISBN: 1118589475 Category : Business & Economics Languages : en Pages : 512
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.
Author: Turan G. Bali Publisher: ISBN: Category : Languages : en Pages : 29
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.
Author: Ajay Bhootra Publisher: ISBN: Category : Languages : en Pages : 44
Book Description
The well-documented negative relationship between idiosyncratic volatility and stock returns is puzzling if investors are risk-averse. However, under prospect theory, while investors are risk-averse in the domain of gains, they exhibit risk-seeking behavior in the domain of losses. Consistent with risk-seeking investors' preference for high volatility stocks in the loss domain, we find that the negative relationship between idiosyncratic volatility and stock returns is concentrated in stocks with unrealized capital losses, but is non-existent in stocks with unrealized capital gains. This finding is robust to control for short-term return reversals and maximum daily return, among other variables.
Author: Kuntara Pukthuanthong Publisher: ISBN: Category : Languages : en Pages :
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.
Author: N. Cakici Publisher: Springer ISBN: 1137359072 Category : Business & Economics Languages : en Pages : 347
Book Description
Risk and Return in Asian Emerging Markets offers readers a firm insight into the risk and return characteristics of leading Asian emerging market participants by comparing and contrasting behavioral model variables with predictive forecasting methods.
Author: Wei Huang
Author: Wei Huang
Author: Xiafei Li
Author: Wei Huang
Author: Fangjian Fu
Author: Turan G. Bali
Author: Turan G. Bali
Author: Ajay Bhootra
Author: Gregory R. Duffee
Author: Kuntara Pukthuanthong
Author: N. Cakici