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Menampilkan postingan dari September, 2016

Applying Corrective AI to Daily Seasonal Forex Trading

  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

Really, Beware of Low Frequency Data

I wrote in a previous article  about why we should backtest even end-of-day (daily) strategies with intraday quote data. Otherwise, the performance of such strategies can be inflated. Here is another brilliant example that I came across recently. Consider the oil futures ETF USO and its evil twin, the inverse oil futures ETF DNO*. In theory, if USO has a daily return of x%, DNO will have a daily return of -x%. In practice, if we plot the daily returns of DNO against that of USO from 2010/9/27-2016/9/9, using the usual consolidated end-of-day data that you can find on Yahoo! Finance or any other vendor, we see that though the slope is indeed -1 (to within a standard error of 0.004), there are many days with significant deviation from the straight line. The trader in us will immediately think "arbitrage opportunities!" Indeed, if we backtest a simple mean reversion strategy on this pair - just buy equal dollar amount of USO and DNO when the sum of their daily returns is less th