A Hidden Markov Model for Statistical Arbitrage in International Crude Oil Futures Markets

Abstract

We study statistical arbitrage strategies in international crude oil futures markets. We analyse strategies that extend classical pairs trading strategies, considering two benchmark crude oil futures (Brent and  WTI) together with the recently introduced Shanghai crude oil futures. We show that the time series of these three futures prices are cointegrated and we introduce a mean-reverting regime-switching process modulated by a hidden Markov chain to model the cointegration spread. By relying on this model and applying online filter-based parameter estimators, we implement and test several statistical arbitrage strategies. Our analysis reveals that statistical arbitrage strategies involving the recently introduced Shanghai futures are profitable even under conservative levels of transaction costs and over different time periods. Statistical arbitrage strategies involving only two of these three futures contracts or the three traditional crude oil futures (Brent, WTI, Dubai) deliver a lower investment performance.

Keywords: Pairs trading, crude oil futures, Shanghai crude oil futures, cointegration, spread process, mean-reverting process, regime switching, stochastic filtering

JEL Classification: C51, C58, G11, G15