By Sergei Belov, Ernest Chan, Nahid Jetha, and Akshay Nautiyal ABSTRACT We applied Corrective AI (Chan, 2022) to a trading model that takes advantage of the intraday seasonality of forex returns. Breedon and Ranaldo (2012) observed that foreign currencies depreciate vs. the US dollar during their local working hours and appreciate during the local working hours of the US dollar. We first backtested the results of Breedon and Ranaldo on recent EURUSD data from September 2021 to January 2023 and then applied Corrective AI to this trading strategy to achieve a significant increase in performance. Breedon and Ranaldo (2012) described a trading strategy that shorted EURUSD during European working hours (3 AM ET to 9 AM ET, where ET denotes the local time in New York, accounting for daylight savings) and bought EURUSD during US working hours (11 AM ET to 3 PM ET). The rationale is that large-scale institutional buying of the US dollar takes place during European working hours to pa
Much has been written about the Post-Earnings Announcement Drift (PEAD) strategy (see, for example, my book ), but less was written about pre -earnings announcement strategies. That changed recently with the publication of two papers. Just as with PEAD, these pre-announcement strategies do not make use of any actual earnings numbers or even estimates. They are based entirely on announcement dates (expected or actual) and perhaps recent price movement. The first one, by So and Wang 2014, suggests various simple mean reversion strategies for US stocks that enter into positions at the market close just before an expected announcement. Here is my paraphrase of one such strategies: 1) Suppose t is the expected earnings announcement date for a stock in the Russell 3000 index. 2) Compute the pre-announcement return from day t-4 to t-2 (counting trading days only). 3) Subtract a market index return over the same lookback period from the pre-announcement return, and call this market-adjusted r