56 Pages Posted: 1 Jul 2015 Last revised: 20 Jun 2017
Date Written: June 19, 2017
Many anomalous portfolios are based on annual accounting characteristics and are rebalanced yearly, ignoring any information during the year. In this paper, we provide a simple dynamic trading strategy to incorporate performance information to rebalance the portfolio monthly. For eight major anomalies, we ﬁnd that the monthly rebalancing portfolios substantially enhance the original anomalies, nearly doubling the average returns while having similar or lower risks. The results are robust to a number of controls. Our ﬁndings indicate that annual information can be more proﬁtable than previously thought, yielding new challenges for their theoretical explanations.
Keywords: Anomaly, low frequency information, technical analysis
JEL Classification: G11, G23
Suggested Citation: Suggested Citation
Han, Yufeng and Huang, Dayong and Zhou, Guofu, Anomalies Enhanced: A Dynamic Trading Strategy (June 19, 2017). Asian Finance Association (AsianFA) 2017 Conference. Available at SSRN: https://ssrn.com/abstract=2624650 or http://dx.doi.org/10.2139/ssrn.2624650