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Quant Investing: Behavioral Strategy

We propose a dynamic allocation of behavioral-factor portfolios, FIN and PEAD, which is designed to capture different sources of misprices (external financing and earnings surprises) in both long- and short-horizons. Equipped with a time-series momentum score, a market-neutral behavioral strategy can generate a Sharpe ratio of 0.66 with beta of -0.14, suggesting that the model can provide a good downside protection while maintaining a superior upside capture.

In more details, FIN factor is a composite of the 1-year net-share-issuance (NSI) and 5-year composite-share-issuance (CSI) measures. FIN is proved to capture predominantly longer-term mispricing and correction (1 year or longer). PEAD factor is adopted here to capture the shorter-horizon mispricing, based on the eponymous post-earnings announcement drift phenomenon. The PEAD observation shows positive earning-surprises subsequently with higher price returns than those with negative earning-surprises.

We then construct a dynamic allocation algorithm based on prior 1-Month, 3-Month, and 6-Month returns. A weighted market-neutral portfolio backtest shows effective protection during 2008-09 financial crisis and 2020 pandemic outbreak.

15 Years Backtest

Short-and Long-Horizon Behavioral Factors, K. Daniel, D. Hirshleifer, and L. Sun, The Review of Financial Studies, 33(4) 2020, 1673-1736
https://academic.oup.com/rfs/article-abstract/33/4/1673/5522378


YC Lin
AVP Quantitative Finance, Gamma Paradigm
LinkedIn

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