The purpose of this paper is to explore trading strategies that exploit investors’ anchoring bias.
This paper forms portfolios based on nearness ratio and other anomaly variables under one- and two-way sorts. The portfolio return series are then regressed on Fama and French three factors to extract abnormal returns.
First is to use anchoring as a technical signal. A strategy that trades against anchoring buys stocks with prices near their 52-week high and sells stocks with prices far below their 52-week high. Based on deciles, the strategy generates a significant value-weighted monthly α of 1.13 percent, after accounting for the market, size, and value factors. Further, the strategy is profitable among both large and small stocks; the trading profit is higher among younger firms and more volatile stocks, but is similar between subsamples formed on number of analysts, level of institutional ownership, and number of institutional owners. The strategy is more profitable following periods of high investor sentiment. Second is to combine anchoring with known anomalies. For a broad set of 26 anomalies, a trading strategy that combines anchoring with the anomalies increases the value-weighted monthly α from an average of 0.61 percent to an average of 1.38 percent. While part of the profits can be attributed to momentum, momentum itself does not explain all the profits.
This paper presents empirical evidence that anchoring bias explains the profitability of a broad set of anomalies and describes practical trading strategies that exploit the anchoring bias.
The paper started when Qingzhong Ma was on faculty at Cornell University and Wei Zhang on faculty at Ithaca College. The authors appreciate helpful discussions, comments, and suggestions received from Levon Goukasian, Thomas Howard, Chunhui Kelvin Zhang, and seminar participants at California State University, Chico.
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