超越法玛-法伦因素:来自短期信号的阿尔法

IF 3.4 3区 经济学 Q1 BUSINESS, FINANCE Financial Analysts Journal Pub Date : 2023-04-13 DOI:10.1080/0015198x.2023.2173492
David Blitz, Matthias X. Hanauer, Iman Honarvar, Rob Huisman, Pim van Vliet
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引用次数: 4

摘要

在传统的资产定价模型中,短期α信号通常被忽略,主要是由于市场摩擦的担忧。然而,本文证明,投资者可以通过将信号组合应用于流动性的全球宇宙并采用先进的买入/卖出交易规则来降低交易成本,从而获得显著的净α。复合模型由短期反转、短期动量、短期分析师修正、短期风险和月度季节性信号组成。由此产生的alpha存在于样本外和出版后时期以及跨地区,转化为只做多的应用程序,对于包含数天的实施滞后是稳健的,并且与传统的Fama-French因素无关。
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Beyond Fama-French Factors: Alpha from Short-Term Signals
Short-term alpha signals are generally dismissed in traditional asset pricing models, primarily due to market friction concerns. However, this paper demonstrates that investors can obtain a significant net alpha by applying a combination of signals to a liquid global universe and with advanced buy/sell trading rules that mitigate transaction costs. The composite model consists of short-term reversal, short-term momentum, short-term analyst revisions, short-term risk, and monthly seasonality signals. The resulting alpha is present in out-of-sample and post-publication periods and across regions, translates into long-only applications, is robust to incorporating implementation lags of several days, and is uncorrelated to traditional Fama-French factors.
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来源期刊
Financial Analysts Journal
Financial Analysts Journal BUSINESS, FINANCE-
CiteScore
5.40
自引率
7.10%
发文量
31
期刊介绍: The Financial Analysts Journal aims to be the leading practitioner journal in the investment management community by advancing the knowledge and understanding of the practice of investment management through the publication of rigorous, peer-reviewed, practitioner-relevant research from leading academics and practitioners.
期刊最新文献
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