Does Realized Skewness Predict the Cross-Section of Equity Returns? PDF Download
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Author: Diego Amaya
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments' time-series and cross-sectional properties. We investigate if this week's realized moments are informative for the cross-section of next week's stock returns. We find a very strong negative relationship between realized skewness and next week's stock returns. A trading strategy that buys stocks in the lowest realized skewness decile and sells stocks in the highest realized skewness decile generates an average weekly return of 19 basis points with a t-statistic of 3.70. Our results on realized skewness are robust across a wide variety of implementations, sample periods, portfolio weightings, and firm characteristics, and are not captured by the Fama-French and Carhart factors. We find some evidence that the relationship between realized kurtosis and next week's stock returns is positive, but the evidence is not always robust and statistically significant. We do not find a strong relationship between realized volatility and next week's stock returns.
Author: Diego Amaya
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments' time-series and cross-sectional properties. We investigate if this week's realized moments are informative for the cross-section of next week's stock returns. We find a very strong negative relationship between realized skewness and next week's stock returns. A trading strategy that buys stocks in the lowest realized skewness decile and sells stocks in the highest realized skewness decile generates an average weekly return of 19 basis points with a t-statistic of 3.70. Our results on realized skewness are robust across a wide variety of implementations, sample periods, portfolio weightings, and firm characteristics, and are not captured by the Fama-French and Carhart factors. We find some evidence that the relationship between realized kurtosis and next week's stock returns is positive, but the evidence is not always robust and statistically significant. We do not find a strong relationship between realized volatility and next week's stock returns.
Author:
Publisher:
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Languages : en
Pages :
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Author:
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Category :
Languages : en
Pages :
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Author: Arthur Lyon Bowley
Publisher: Franklin Classics Trade Press
ISBN: 9780344299537
Category :
Languages : en
Pages : 404
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Book Description
This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Author: Turan G. Bali
Publisher: John Wiley & Sons
ISBN: 1118589661
Category : Business & Economics
Languages : en
Pages : 512
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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: Ilan Cooper
Publisher:
ISBN:
Category :
Languages : en
Pages : 79
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Book Description
We derive a parsimonious three-factor asset pricing model (cross-sectional CAPM, CS-CAPM) in which stock return dispersion (realized cross-sectional variance of long-short equity portfolios) and stock return skewness (realized cross-sectional skewness of equity portfolios) are the driving forces in pricing cross-sectional equity risk premia. Market segmentation leads these two factors to be priced in equilibrium. The model offers a large fit for the joint cross-sectional risk premia associated with 16 prominent CAPM anomalies, with explanatory ratios above 40%. The CS-CAPM compares favorably with multifactor models widely used in the literature. The cross-sectional factors are not subsumed by traditional macro risk factors.
Author: Torben Gustav Andersen
Publisher: Springer Science & Business Media
ISBN: 3540712976
Category : Business & Economics
Languages : en
Pages : 1045
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Book Description
The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
Author: Norman R. Swanson
Publisher: MDPI
ISBN: 303650852X
Category : Business & Economics
Languages : en
Pages : 196
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Book Description
Recently, considerable attention has been placed on the development and application of tools useful for the analysis of the high-dimensional and/or high-frequency datasets that now dominate the landscape. The purpose of this Special Issue is to collect both methodological and empirical papers that develop and utilize state-of-the-art econometric techniques for the analysis of such data.
Author: James L. Davis
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Using a database that is free of survivorship bias, this paper finds that book-to-market equity, earnings yield and cash flow yield have significant explanatory power with respect to the cross-section of realized stock returns during the period from July, 1940 to June, 1963. There is a strong January seasonal in the explanatory power of these variables, even though small stocks are, by construction, excluded from the sample.
Author: Bumjean Sohn
Publisher:
ISBN:
Category :
Languages : en
Pages : 76
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Book Description
We discuss the nature of risk valid factors should represent. The Campbell's (1993) ICAPM extended with heteroskedastic asset returns guides us to identify the risk; we show that many of empirically well-established factors contain information about the future changes in the investment opportunity set and that is why these factors are strongly priced across assets. Specifically, we show that size, momentum, liquidity (trading strategy based factors), industrial production growth, and inflation (macroeconomic factors) factors as well as both short- and long-run market volatility factors are significantly priced because they all have information about the changes in the future market volatility which characterizes the future investment opportunity set in our model. The time-series studies show that the above-mentioned factors do predict the market volatility and the cross-sectional studies show that these factors are priced due to their predictability on the future market volatility. Both studies are consistent and strongly support the relationship between the stock market volatility and the priced factors. By revealing the nature of risk the empirically well-established factors represent, we provide an explanation why we observe so many empirically strong factors in the literature.
