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 mentioned in various places that Alphacet Discovery is an industrial strength integrated platform for backtesting and implementing quantitative trading strategies. But of course, it has many competitors, one of which is a relatively new company called Deltix . Deltix has the distinction of offering a full Matlab interface, which is convenient if you are already a Matlab programmer. (Full disclosure: I previously have a consulting relationship with Alphacet, but have none with Deltix.) There is also a new website for sharing trading strategy software called Quantonomics . In the words of its founder Joshua, the goal is to "connect programmers and stock traders". Joshua also told me that he will create a custom application on his site for any of you readers as a gift! A colleague of mine in Singapore, Dr. Li Haksun, who was previously a quant with UBS and BNP Paribas, is offering a course on quantitative trading strategy in July. It covers more theoretical concepts than my