Langsung ke konten utama


Menampilkan postingan dari Desember, 2009

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

Selecting tradeable pairs: which measure to use?

A guest blog by Paul Farrington One of the most important factors in statistical arbitrage pairs trading is the selection of the paired instruments.  We can use basic heuristics to guide us, such as grouping stocks by industry in the anticipation that stocks with similar fundamental characteristics will share factor risk and tend to exhibit co-movement.  But this still leaves us with potentially thousands of combinations.  There are some statistical techniques we can use to quantify the tradeability of a pair: one approach is to calculate the correlation coefficient of each pair's return series. Another is to consider cointegration measures on the ratio of the prices, to see if it remains stationary over time. In this article I briefly summarise the alternative approaches and apply them to a universe of stock pairs in the oil and gas industry.  To measure how effective each measure is in real world trading, I back test the pairs using a simple means reversion system, then regress t

Public service announcements for quants

   1.  Conference on 'Computational Topics in Finance', February 19/20, 2010, National University of Singapore. The topics will include using R/Rmetrics in finance, but the conference is by no means confined to R. See    2.  Consulting position (6-month renewable contract) available at a major Canadian bank in Toronto:  research in  various mathematical algorithms used for pricing of interest rate derivative instruments like swaps, caps, swaptions, FRAs. Please contact their recruiter at    3.  A free copy of Chapter 8 of " High Probability ETF Trading " which I mentioned here is now available for download .

Are financial speculations really "harmful human activities"?

It is worrisome when not one but two eminent economists denounced financial speculation as "harmful human activities" in the short space of 2 weeks. (See Paul Krugman's column here and Robert Frank's here .) It is more worrisome when their proposed cure to this evil is to apply a financial transaction tax to all financial transactions. Granted, you can always find this or that situation when financial speculation did cause harm. Maybe speculation did cause the housing bubble. Maybe speculation did cause an energy price bubble. In the same vein, you can also argue that driving is a harmful human activity because cars did cause a few horrific traffic accidents. No, we can't focus on a few catastrophes if we were to argue that financial speculation is harmful. We have to focus on whether it is harmful on average . And on this point, I haven't seen our eminent economists present any scientific evidence. On the other hand, as an ex-physicist and an Einstein-devot