Traditional asset pricing models do not account for short-term alpha signals. This study finds that investors can obtain net alpha by combining such signals and mitigating transaction costs. This alpha is uncorrelated with Fama–French factors.
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Beyond Fama-French Factors: Alpha from Short-Term Signals (In Practice)
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Abstract
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.