The Cross-Section of Volatility and Expected Returns

56 Pages Posted: 5 Apr 2005

See all articles by Andrew Ang

Andrew Ang

BlackRock, Inc

Robert J. Hodrick

Columbia University - Columbia Business School, Finance; National Bureau of Economic Research (NBER)

Yuhang Xing

Rice University

Xiaoyan Zhang

Tsinghua University - PBC School of Finance

Multiple version iconThere are 2 versions of this paper

Abstract

We examine how volatility risk, both at the aggregate market and individual stock level, is priced in the cross-section of expected stock returns. Stocks that have past high sensitivities to innovations in aggregate volatility have low average returns. We also find that stocks with past high idiosyncratic volatility have abysmally low returns, but this cannot be explained by exposure to aggregate volatility risk. The low returns earned by stocks with high exposure to systematic volatility risk and the low returns of stocks with high idiosyncratic volatility cannot be explained by the standard size, book-to-market, or momentum effects, and are not subsumed by liquidity or volume effects.

Keywords: Systematic risk, stochastic volatility, idiosyncratic volatility

JEL Classification: G12, G13

Suggested Citation

Ang, Andrew and Hodrick, Robert J. and Xing, Yuhang and Zhang, Xiaoyan, The Cross-Section of Volatility and Expected Returns. Available at SSRN: https://ssrn.com/abstract=681343

Andrew Ang (Contact Author)

BlackRock, Inc ( email )

55 East 52nd Street
New York City, NY 10055
United States

Robert J. Hodrick

Columbia University - Columbia Business School, Finance ( email )

3022 Broadway
New York, NY 10027
United States

National Bureau of Economic Research (NBER)

365 Fifth Avenue, 5th Floor
New York, NY 10016-4309
United States

Yuhang Xing

Rice University ( email )

6100 South Main Street
Houston, TX 7705-1892
United States

Xiaoyan Zhang

Tsinghua University - PBC School of Finance ( email )

No. 43, Chengdu Road
Haidian District
Beijing 100083
China

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
4,961
Abstract Views
34,386
Rank
2,118
PlumX Metrics