Trading futures spreads: an application of correlation and threshold filters

A clear motivation for this paper is the investigation of a correlation filter to improve the return/risk performance of spread trading models. A further motivation for this paper is the extension of trading futures spreads beyond the 'Fair Value' type of model used by Butterworth and Holmes (2002). The trading models tested are the following: the cointegration 'fair value' approach; reverse moving average (of which the results of the 20-day model are shown here); traditional regression techniques; and Neural Network Regression. Also shown is the effectiveness of two types of filter: a standard filter and a correlation filter on the trading rule returns. Results show that the best model for trading the WTI-Brent spread is the MACD model, which proved to be profitable, both in- and out-of-sample. This is evidenced by out-of-sample annualised returns of 26.35% for the standard filter and 26.15% for the correlation filter (inclusive of transactions costs).