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AFA2019会议论文(51):Market Risk Factors

2019-2-20 17:03| 发布者: sujiaoshou| 查看: 410| 评论: 0|原作者: 金融经济学|来自: 金融经济学

摘要: AFA2019会议论文(51):Market Risk Factors

AFA2019会议论文(51):Market Risk Factors

金融经济学 1周前

 

1、Granularity and (Downside) Risk in Equity Markets

 

Eric Ghysels,University of North Carolina

 

Abstract

The U.S. 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 heterogeneous 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.

 

原文链接:

https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFA2019&paper_id=1611

 

 

2、Hedging Factor Risk

 

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 all factors perform about as well as high beta versions despite a significant spread in betas, hence a long short portfolio can hedge factor risks without a reduction in expected return. Low beta versions of the reduced form factors have strong positive alphas with respect to the factors themselves, and the beta vs expected return line is flat for most factors pointing to a mismatch in exposure and expected return. For the macroeconomic factors, we show that hedging the factors also hedges business cycle risk because hedge portfolios reduce exposure to recessions. We study implications both for optimal portfolio formation and for understand the economic mechanisms for generating equity risk premiums.

 

原文链接:

https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFA2019&paper_id=1706

 

 

3Are 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.

 

原文链接:

https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFA2019&paper_id=1600

 

 

4Size and Value in China

 

Jianan Liu,University of Pennsylvania

Robert Stambaugh,University of Pennsylvania

Yu Yuan,Mingshi Investment Management Co., Ltd.

 

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.

 

原文链接:

https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=AFA2019&paper_id=1283

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