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
I have written a lot in the past about the cointegration of ETF pairs, and how this condition can lead to profitable pairs trading. However, as every investment advisor could have told you, past cointegration is no guarantee of future cointegration. Often, cointegration for a pair breaks down for an extended period, maybe as long as a half a year or more. Naturally, trading this pair during this period is a losing proposition, but abandoning such a pair completely is also unsatisfactory, since cointegration often mysteriously returns after a while. A case in point is the ETF pair GLD-GDX . When I first tested it in 2006, it was an excellent candidate for pair trading, and I not only traded it in my personal portfolio, but we traded it in our fund too. Unfortunately, it went haywire in 2008. We promptly abandoned it, only to see the strategy recovered sharply in 2007. So the big question is: how do we know whether the loss of cointegration is temporary, and how do we know when to resume