Volatility and the Cross-Section of Equity Returns

Volatility and the Cross-Section of Equity Returns PDF Author: Ruslan Goyenko
Publisher:
ISBN:
Category :
Languages : en
Pages : 55

Get Book Here

Book Description
A number of papers document a strong negative relation between idiosyncratic volatility and risk-adjusted stock returns. Using IHS Markit data on indicative borrowing fees, we show that stocks with high idiosyncratic volatility are far more likely to be hard-to-borrow than stocks with low idiosyncratic volatility. When hard-to-borrow stocks are excluded, the relation between idiosyncratic volatility and stock returns disappears. The relation between idiosyncratic volatility and stocks returns is more accurately described as a relation between being hard-to-borrow and stock returns.

Volatility and the Cross-Section of Equity Returns

Volatility and the Cross-Section of Equity Returns PDF Author: Ruslan Goyenko
Publisher:
ISBN:
Category :
Languages : en
Pages : 55

Get Book Here

Book Description
A number of papers document a strong negative relation between idiosyncratic volatility and risk-adjusted stock returns. Using IHS Markit data on indicative borrowing fees, we show that stocks with high idiosyncratic volatility are far more likely to be hard-to-borrow than stocks with low idiosyncratic volatility. When hard-to-borrow stocks are excluded, the relation between idiosyncratic volatility and stock returns disappears. The relation between idiosyncratic volatility and stocks returns is more accurately described as a relation between being hard-to-borrow and stock returns.

Cross-Section of Equity Returns

Cross-Section of Equity Returns PDF Author: Bumjean Sohn
Publisher:
ISBN:
Category :
Languages : en
Pages : 76

Get Book Here

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.

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

The negative relationship between the cross-section of expected returns and lagged idiosyncratic volatility. The German stock market 1990-2016 PDF Author: Lasse Homann
Publisher: GRIN Verlag
ISBN: 3346153215
Category : Business & Economics
Languages : en
Pages : 38

Get Book Here

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.

Empirical Asset Pricing

Empirical Asset Pricing PDF Author: Turan G. Bali
Publisher: John Wiley & Sons
ISBN: 1118095049
Category : Business & Economics
Languages : en
Pages : 517

Get Book Here

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.

Leverage and the Cross-Section of Equity Returns

Leverage and the Cross-Section of Equity Returns PDF Author: Hitesh Doshi
Publisher:
ISBN:
Category :
Languages : en
Pages : 61

Get Book Here

Book Description
Building on the theoretical asset pricing literature, we examine the role of market risk and the size, book-to-market (BTM), and volatility anomalies in the cross-section of unlevered equity returns. Compared with levered (stock) returns, the unlevered market beta plays a more important role in explaining the cross-section of unlevered equity returns, even when we control for size and BTM. The size effect is weakened, while the value premium and the volatility puzzle virtually disappear for unlevered returns. We show that leverage induces heteroskedasticity in returns. Unlevering returns removes this pattern, which is otherwise difficult to address by controlling for leverage in regressions.

Cointegration, Causality, and Forecasting

Cointegration, Causality, and Forecasting PDF Author: Halbert White
Publisher: Oxford University Press, USA
ISBN: 9780198296836
Category : Business & Economics
Languages : en
Pages : 512

Get Book Here

Book Description
A collection of essays in honour of Clive Granger. The chapters are by some of the world's leading econometricians, all of whom have collaborated with and/or studied with both) Clive Granger. Central themes of Granger's work are reflected in the book with attention to tests for unit roots and cointegration, tests of misspecification, forecasting models and forecast evaluation, non-linear and non-parametric econometric techniques, and overall, a careful blend of practical empirical work and strong theory. The book shows the scope of Granger's research and the range of the profession that has been influenced by his work.

The Information Content in Implied Idiosyncratic Volatility and the Cross-Section of Stock Returns

The Information Content in Implied Idiosyncratic Volatility and the Cross-Section of Stock Returns PDF Author: Dean Diavatopoulos
Publisher:
ISBN:
Category :
Languages : en
Pages : 33

Get Book Here

Book Description
Current literature is inconclusive as to whether idiosyncratic risk influences future stock returns and the direction of the impact. Prior studies are based on historical realized volatility. Implied volatilities from option prices represent the market's assessment of future risk and are likely a superior measure to historical realized volatility. We use implied idiosyncratic volatilities on firms with traded options to examine the relation between idiosyncratic volatility and future returns. We find a strong positive link between implied idiosyncratic risk and future returns. After considering the impact of implied idiosyncratic volatility, historical realized idiosyncratic volatility is unimportant. This performance is strongly tied to small size and high book-to-market equity firms.

Idiosyncratic return volatility in the cross-section of stocks

Idiosyncratic return volatility in the cross-section of stocks PDF Author: Namho Kang
Publisher:
ISBN:
Category : Stocks
Languages : en
Pages : 32

Get Book Here

Book Description


Anchoring Bias Idiosyncratic Volatility and the Cross-section of Stock Returns

Anchoring Bias Idiosyncratic Volatility and the Cross-section of Stock Returns PDF Author: Cedric T. Luma Mbanga
Publisher:
ISBN:
Category : Stocks
Languages : en
Pages : 120

Get Book Here

Book Description


Good Volatility, Bad Volatility and the Cross-Section of Stock Returns

Good Volatility, Bad Volatility and the Cross-Section of Stock Returns PDF Author: Tim Bollerslev
Publisher:
ISBN:
Category :
Languages : en
Pages : 77

Get Book Here

Book Description
Based on intraday data for a large cross-section of individual stocks and newly developed econometric procedures, we decompose the realized variation for each of the stocks into separate so-called realized up and down semi-variance measures, or “good” and “bad” volatilities, associated with positive and negative high-frequency price increments, respectively. Sorting the individual stocks into portfolios based on their normalized good minus bad volatilities results in economically large and highly statistically significant differences in the subsequent portfolio returns. These differences remain significant after controlling for other firm characteristics and explanatory variables previously associated with the cross-section of expected stock returns.