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Identifying Hedge Fund Skill by Using Peer Cohorts

机译:使用PEER COHORTS识别对冲基金技能

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Disclosures: The authors have no conflicts of interest to declare. The content of this article reflects the views of the authors and not necessarily the views of BlueCove Limited.Editor's Note:Submitted 2 September 2020. Accepted 6 January 2021 by Moshe Arye Milevsky This article was externally reviewed using our double-blind peer-review process. When the article was accepted for publication, the authors thanked the reviewers in their acknowledgments. Nicole M. Boyson and one anonymous reviewer were the reviewers for this article.We propose a cohort model that evaluates hedge funds against peer groups executing similar investment strategies formed by using return correlations. Our method improves the identification of skilled managers, as evidenced by a strong ability to explain hedge fund returns out-of-sample, with cohort alpha being more persistent than alpha based on the widely accepted seven-factor model. A hedge fund-of-funds analysis found significant performance enhancement from exposure to the best funds within each cohort. The cohort approach can be used to enhance the construction of hedge fund-of-funds portfolios by isolating strategy groupings as well as the best managers within each group.
机译:披露:提交人没有申报利益冲突。本文的内容反映了作者的意见,不一定是BlueCove Limited.Editor的注意事项:提交2020年9月2日。由Moshe Arye Milevsky接受了2021年1月6日使用我们的双盲同行评审过程进行了外部审查本文。当文章被接受出版时,提交人感谢审稿人的致谢。妮可M. Boyson和一个匿名评论家是这篇文章的审稿人。我们提出了一个队列模型,评估对冲基金的同行团体,执行通过返回相关性形成的类似投资策略。我们的方法改善了熟练管理人员的识别,通过强大的解释对冲基金的能力证明了返回样本,基于广泛接受的七因素模型,群组alpha比alpha更持久。对冲基金基金会分析发现,从接触每个群组内的最佳资金都有显着的性能增强。队列方法可用于通过隔离战略分组以及每组内的最佳管理人员来增强对冲基金投资组合的构建。

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