This website uses cookies.

By clicking the "Accept" button or continuing to browse our site, you agree to first-party and session-only cookies being stored on your device to enhance site navigation and analyze site performance and traffic. For more information on our use of cookies, please see our Privacy Policy.

« Back to Results

Market Risk Factors

Paper Session

Sunday, Jan. 6, 2019 8:00 AM - 10:00 AM

Hilton Atlanta, Salon West
Hosted By: American Finance Association
  • Chair: Jianfeng Yu, Tsinghua University

Granularity and (Downside) Risk in Equity Markets

Eric Ghysels
,
University of North Carolina

Abstract

The US equities market price process is largely driven by the information set and actions of large institutional investors, not individual retail investors. Using quarterly 13-F holdings, we construct the Herfindahl-Hirschman Index (HHI) of institutional investor concentration as a measure of granularity. Our contributions are both empirical and theoretical. We provide a comprehensive study of how granularity affects: (1) the cross-section of returns, (2) conditional variances across stocks and (3) downside risk. We find that constructing a low-HHI minus high-HHI portfolio produces an annualized return of 5.6 %. Using an approach advocated by Koijen and Yogo, we document that the cross-section of HHI portfolios can be explained by a conditional asset pricing model involving heterogenous investor demands driven by time-varying beliefs over asset characteristics. We document the adverse impact that investor ownership concentration has on both conditional volatility, and critically, a robust set of downside risk measures at both the portfolio and the firm level.

Hedging Risk Factors

Bernard Herskovic
,
University of California-Los Angeles
Alan Moreira
,
University of Rochester
Tyler Muir
,
University of California-Los Angeles

Abstract

Standard risk factors can be hedged with minimal reduction in average return. This is true for "macro" factors such as industrial production, unemployment, and credit spreads, as well as for "reduced form" asset pricing factors such as value, momentum, or profitability. Low beta versions of the factors perform close to as well as high beta versions, hence a long short portfolio can hedge factor exposure with little reduction in expected return. For the reduced form factors this mismatch between factor exposure and expected return generates large alphas. For the macroeconomic factors, hedging the factors also hedges business cycle risk by significantly lowering exposure to consumption, GDP, and NBER recessions. We study implications both for optimal portfolio formation and for understanding the economic mechanisms for generating equity risk premiums.

Are Cross-Sectional Predictors Good Market-Level Predictors?

Joseph Engelberg
,
University of California-San Diego
David McLean
,
Georgetown University
Jeffrey Pontiff
,
Boston College
Matthew Ringgenberg
,
University of Utah

Abstract

Firm-level variables that predict cross-sectional stock returns, such as price-to-earnings and book-to-market, are often aggregated and used to predict time-series market returns. We extend this literature and limit the data-snooping bias by using a near-complete population of the literature’s cross-sectional return predictors. Our tests reject the null of no predictability at the annual horizon in-sample. Moreover, we find the literature has ignored several cross-sectional variables–such as change in asset turnover and co-skewness–that contain strong in-sample predictability. When we consider out-of-sample testing, however, we find little evidence that cross-sectional predictors make good market-level predictors.

Size and Value in China

Jianan Liu
,
University of Pennsylvania
Robert Stambaugh
,
University of Pennsylvania
Yu Yuan
,
Mingshi Investment Management Co.

Abstract

We construct size and value factors in China. The size factor excludes the smallest 30% of firms, which are companies valued significantly as potential shells in reverse mergers that circumvent tight IPO constraints. The value factor is based on the earnings-price ratio, which subsumes the book-to-market ratio in capturing all Chinese value effects. Our three-factor model strongly dominates a model formed by just replicating the Fama and French (1993) procedure in China. Unlike that model, which leaves a 17% annual alpha on the earnings-price factor, our model explains most reported Chinese anomalies, including profitability and volatility anomalies.
Discussant(s)
Ralph Koijen
,
University of Chicago
Kent Daniel
,
Columbia University
Amit Goyal
,
University of Lausanne
Jun Qian
,
Fudan University
JEL Classifications
  • G1 - General Financial Markets