Hidden Markov Regimes for Crude Oil Futures Statistical Arbitrage

Summary

The study examines pairs-trading extensions across Brent, WTI, and Shanghai crude oil futures. It reports that the three price series are cointegrated and models their resulting spread as mean-reverting with regimes governed by a hidden Markov chain. Online filter-based parameter estimates are used to implement and test statistical-arbitrage strategies.

The reported strategies involving Shanghai crude oil futures were profitable across different periods and under conservative transaction-cost assumptions. Strategies using the traditional Brent, WTI, and Dubai futures did not produce profitable opportunities in the analysis. These are study-specific historical findings, and the excerpt gives no details on sample dates, execution assumptions, or out-of-sample validation. It therefore motivates investigation of Shanghai crude as a relative-value instrument without establishing that the result will persist or generalize to other market conditions.

Key ideas

• The study models cointegrated crude oil futures prices through their spread.
• The spread is represented as a mean-reverting process whose regime follows a hidden Markov chain.
• Online filtering estimates model parameters for the tested statistical-arbitrage strategies.
• Strategies involving Shanghai crude futures were reported profitable across periods and conservative transaction costs.
• The tested traditional crude futures combination did not yield profitable opportunities, and the excerpt does not establish future performance.

Tags

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


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









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.

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