The Effect of Kurtosis on the Cross-section of Stock Returns PDF Download
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Author: Abdullah Al Masud
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
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Book Description
In this study, I show an e ect of the statistical fourth moment on stock returns. In the mean-variance framework, rational investors follow two strategies: optimize the mean-variance of return and diversify the portfolio. Regarding the first approach, investors intend to generate the maximum level of return while facing a constant level of risk (or, the standard deviation) of return. It is possible that form specific risk can be concentrated in the portfolio. However, diversification of the assets can eliminate that (idiosyncratic) risk from the portfolio. After a long period of time, in a diversified portfolio the shape of the return distribution appears to be peaked around the average value of the return compared with that of the typical shape of the return dis- tribution. If investors have a preference for skewness in their returns, they also can produce peakedness in the shape of the distribution. The statistical fourth moment (kurtosis) measures the magnitude of peakedness of the distribution. As the kurtosis of the distribution increases the distribution will appear more peaked. I find evidence that kurtosis positively and significantly predicts future stock returns over the period 1981-2011. The effect remains after controlling for other factors in multivariate regressions.
Author: Abdullah Al Masud
Publisher:
ISBN:
Category :
Languages : en
Pages : 21
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Book Description
In this study, I show an e ect of the statistical fourth moment on stock returns. In the mean-variance framework, rational investors follow two strategies: optimize the mean-variance of return and diversify the portfolio. Regarding the first approach, investors intend to generate the maximum level of return while facing a constant level of risk (or, the standard deviation) of return. It is possible that form specific risk can be concentrated in the portfolio. However, diversification of the assets can eliminate that (idiosyncratic) risk from the portfolio. After a long period of time, in a diversified portfolio the shape of the return distribution appears to be peaked around the average value of the return compared with that of the typical shape of the return dis- tribution. If investors have a preference for skewness in their returns, they also can produce peakedness in the shape of the distribution. The statistical fourth moment (kurtosis) measures the magnitude of peakedness of the distribution. As the kurtosis of the distribution increases the distribution will appear more peaked. I find evidence that kurtosis positively and significantly predicts future stock returns over the period 1981-2011. The effect remains after controlling for other factors in multivariate regressions.
Author: Nima Ebrahimi
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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Book Description
We show that exposure to the risk of kurtosis in oil market drives the cross-section of stock returns from 1996 to 2014. The average monthly difference between the return of portfolio of stocks with low exposure and high exposure to the risk of kurtosis is -0.37%, showing that higher exposure to oil's kurtosis risk will be penalized by lower average returns. We are able to confirm the significance of kurtosis risk within the statistical framework of Carhart 4-factor model. In contrast to the skewness risk, which is only a significant player in some of the sub-periods, kurtosis risk is keeping its significance through all sub-periods, as well as after taking market moments into account and within different maturities. The significance of the risk of skewness gets more evident moving from shorter to longer maturities. The risk of volatility, which has been shown to be a significant-priced risk in the cross-section of stock returns in literature, loses its significance after controlling for the third and fourth moments.
Author: Cheng-Few Lee
Publisher: Springer
ISBN: 9781461477495
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
The Handbook of Financial Econometrics and Statistics provides, in four volumes and over 100 chapters, a comprehensive overview of the primary methodologies in econometrics and statistics as applied to financial research. Including overviews of key concepts by the editors and in-depth contributions from leading scholars around the world, the Handbook is the definitive resource for both classic and cutting-edge theories, policies, and analytical techniques in the field. Volume 1 (Parts I and II) covers all of the essential theoretical and empirical approaches. Volumes 2, 3, and 4 feature contributed entries that showcase the application of financial econometrics and statistics to such topics as asset pricing, investment and portfolio research, option pricing, mutual funds, and financial accounting research. Throughout, the Handbook offers illustrative case examples and applications, worked equations, and extensive references, and includes both subject and author indices.
Author: Ruifeng Liu
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
We study the robust measure of higher moments and employ their predictive power for future financial returns. In Chapter 1, we propose a new quantile-based measure of kurtosis. Then in Chapters 2 and 3, we provide an empirical analysis of the predictive information of robust volatility, robust skewness, and robust kurtosis for the cross-section of international stock index returns and cryptocurrency returns, respectively. In Chapter 1, we introduce robust kurtosis, which is a new quantile-based measure for the kurtosis of financial returns that is robust to outliers. Robust kurtosis is equivalent to the traditional moment-based kurtosis for the normal distribution, whereas for fat-tailed distributions it converges to the moment-based measure as the return horizon increases. We assess its asymptotic properties as well as its finite-sample properties under different distributional specifications. In Chapter 2, we provide an empirical analysis of the predictive information of robust conditional kurtosis for a large cross-section of international stock index returns. Using portfolio sorts and Fama-MacBeth cross-sectional regressions, we find that robust kurtosis carries a significant negative premium: higher robust kurtosis is related to lower future stock returns, especially for developed markets. This contrasts with the significant positive premium associated with robust skewness, especially for emerging markets. In Chapter 3, we provide an empirical analysis of the predictive information of robust conditional volatility, skewness, and kurtosis for a large cross-section of cryptocurrency returns. Using portfolio sorts and Fama-MacBeth cross-sectional regressions, we find that robust volatility carries a significant negative premium: higher robust volatility is related to lower future cryptocurrency returns, especially for one-week ahead returns. This contrasts with the significant positive premium associated with robust skewness, especially for one-day ahead returns.
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: 蘇昱翔
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
The realized moments innovations are calculated by the intraday data to the weekly frequency. From realized moments innovations we investigate if these variables are informative for the future stock returns. We find that realized skewness innovations are negative with next week's stock returns. Our work shows that makes portfolios with buying the stocks in highest previous realized moments innovations and selling the stocks in lowest previous realized moments innovations can make good profit. Our realized moments innovations are robust some firm characteristics can predict still signicance over two weeks. We do not find evidence that realized volatility innovations, realized kurtosis innovations and next week's stock return have the relationship..
Author: Ronald Jared DeLisle
Publisher:
ISBN:
Category :
Languages : en
Pages : 100
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Book Description
ABSTRACT: This dissertation examines if information extracted from the options markets is priced in the cross-section of equity returns and whether or not this information is a systematic risk factor. Several versions of the Intertemporal Capital Asset Pricing Model predict that changes in aggregate volatility are priced into the cross-section of stock returns. Literature confirms that changes in expected future market volatility are priced into the cross-section of stock returns. Several of these studies use the VIX Index as proxy for future market volatility, and suggest that it is a risk factor. However, prior studies do not test whether asymmetric volatility affects if firm sensitivity to changes in VIX is related to risk, or is just a characteristic uniformly affecting all firms. The first chapter of my dissertation examines the asymmetric relation of stock returns and changes in VIX. The study finds that sensitivity to VIX innovations affects returns when volatility is rising, but not when it is falling. When VIX rises this sensitivity is a priced risk factor, but when it falls there is a positive impact on all stocks irrespective of VIX loadings. The second essay of my dissertation uses the second, third, and fourth moments of the risk-neutral density extracted from options on the S & P 500 as the proxy for changes in the expected future market return distribution rather than just the VIX index. The VIX index, while easily obtained, contains limited information due to its construction. The risk-neutral moments map one-to-one to the real-world volatility smile from market options, and contain all the information in the cross-section of market option moneyness and provide a richer proxy for changes in expected future market return distribution. The analyses find that positive change in risk-neutral skewness is a risk-factor and that change in risk-neutral kurtosis is not. The evidence for change in risk-neutral volatility being a risk factor, however, is ambiguous.
Author: Zhongxiang Xu
Publisher:
ISBN:
Category :
Languages : en
Pages : 41
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Book Description
This paper develops a new measure of return asymmetry, following Patil et al. (2012). We demonstrate that the return asymmetry measure helps explain the cross section of stock returns. Consistent with results in Barberis and Huang (2008), our empirical findings show that stocks with high return asymmetry exhibit low expected returns. The negative relation between return asymmetry and the cross section of stock returns persists for up to the 12-month forecast horizon and remains robust after controlling for the effects of skewness.
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: 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.
