Langsung ke konten utama


Menampilkan postingan dari Januari, 2011

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

High frequency trading ideas

I just started reading Larry Harris' book " Trading and Exchanges " (thanks to Max Dama 's glowing book review) and already a couple of potential high frequency trading techniques stood out: " Quote matching " - a technique whereby front-runners place a limit buy order just a cent (for stocks) higher than the best bid price. If the order is filled, they then place a limit sell order just a cent lower than the best ask. Assuming the best bid-ask quotes don't move, the worst they can do is to lose 1 cent by selling the share back to the best bidder, while the most profit they can make is the bid-ask spread plus rebates for providing liquidity minus 2 cents by having the sell long limit order filled. This could work out quite profitably if the bid-ask spread is wide. But of course, the best bid-ask do change constantly, so front-runners would need to cancel and correct their limit orders constantly, and the optimal algorithm for doing this could get quite c

Shorting the VIX calendar spread

Lately there were a few interesting discussions in the  blogosphere  on the profitability of shorting the VXX-VXZ spread. (See Quantum Blog and The Speculator's Ball .) For background, VXX is an ETN that tracks the first and second month of the VIX future, which in turn tracks the VIX volatility index, which in turn tracks the volatility of SPX. VXZ is the ETN that tracks the 4th - 7th months of the VIX future. During the period 2009-2010, there were 2 different reasons why shorting this "calendar spread" was profitable: 1) The VIX futures were/are in contango: i.e. the back months' futures are more expensive than the front months'. 2) The volatility of SPX was decreasing with time. However, some traders seem to think that either one of these conditions is enough to ensure the profitability of shorting a calendar spread.  It is not. (Otherwise, life as a futures trader would be too easy!) To see this, let's resort to a simplistic linear approximation to a mod