文章基本信息

标题：Are higher-order factors useful in pricing the cross-section of hedge fund returns?
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作者：Caio Almeida ; Elaine Fang
期刊名称：Brazilian Review of Finance
印刷版ISSN：1984-5146
出版年度：2019
卷号：17
期号：2
页码：1-37
DOI：10.12660/rbfin.v17n2.2019.78017
出版社：Link to the Brazilian Society of Finance
摘要：This paper investigates hedge funds’ exposures to various risk factors across different investment strategies through models with both linear and second-order factors. We extend the analysis from an augmented linear model based on Fama & French (1993) and Fung & Hsieh (2001) to second-order models that include all quadratic and interaction terms by adopting a novel multistep strategy that combines the variable selection capabilities of the LASSO regression with the Fama & MacBeth (1973) two-step method. We find that, for some strategies, several quadratic and interaction terms are statistically significant. Nonetheless, there is no evidence that the second-order models have more overall explanatory or predictive power than the linear model. Moreover, while both linear and second-order models perform well for directional funds (like emerging markets, event driven and managed futures), missing factors may still remain for semi-directional funds, such as fund of funds, long/short equity hedge and multi-strategy.
关键词：Hedge Fund Performance; LASSO; Risk Factors; Cross-Section of Returns