A hidden Markov model for statistical arbitrage in international crude oil futures markets

TL;DR

This paper develops a hidden Markov model-based statistical arbitrage strategy for international crude oil futures, demonstrating profitability of Shanghai futures and highlighting their potential for global investors.

Contribution

The study introduces a novel regime-switching cointegration model for crude oil futures and applies it to develop profitable arbitrage strategies involving Shanghai futures.

Findings

Shanghai futures are profitable for arbitrage strategies.

Traditional Brent and WTI futures do not yield profitable opportunities.

The model effectively captures regime changes in crude oil markets.

Abstract

In this work, we study statistical arbitrage strategies in international crude oil futures markets. We analyse strategies that extend classical pairs trading strategies, considering the two benchmark crude oil futures (Brent and WTI) together with the newly introduced Shanghai crude oil futures. We document that the time series of these three futures prices are cointegrated and we model the resulting cointegration spread by a mean-reverting regime-switching process modulated by a hidden Markov chain. By relying on our stochastic model and applying online filter-based parameter estimators, we implement and test a number of statistical arbitrage strategies. Our analysis reveals that statistical arbitrage strategies involving the Shanghai crude oil futures are profitable even under conservative levels of transaction costs and over different time periods. On the contrary, statistical arbitrage strategies involving the three traditional crude oil futures (Brent, WTI, Dubai) do not yield profitable investment opportunities. Our findings suggest that the Shanghai futures, which has already become the benchmark for the Chinese domestic crude oil market, can be a valuable asset for international investors.