Oil Futures and Arbitrage: The Shanghai Case
For decades, the global price of oil has been determined primarily in two places: London and New York. On one side, North Sea Brent; on the other, American WTI. Then came Dubai, with its Dubai Crude, and finally Shanghai.
When China launched its crude oil futures contracts in 2018, many analysts viewed them as little more than a geopolitical symbol: Beijing’s attempt to establish an alternative oil benchmark to Western ones. But today, those contracts are attracting attention for a very different reason: they may offer profit opportunities that have all but disappeared in mature markets.
This is the conclusion of a new study (“A hidden Markov model for statistical arbitrage in international crude oil futures markets”) published in the Journal of Banking and Finance by Francesco Rotondi of the Department of Finance at Bocconi University, together with Viviana Fanelli (University of Foggia) and Claudio Fontana (University of Padua). The research shows that the prices of Brent, WTI, and Shanghai crude oil futures still move with certain mutual “imperfections.” And it is precisely these small misalignments that can become arbitrage opportunities for quantitative investors.
In other words: when one of the three markets moves “too much” relative to the others, there is a good chance it will quickly return to equilibrium. Those who manage to catch that moment can profit from the price correction.
“Strategies involving the recently introduced Shanghai futures can be profitable even under conservative levels of transaction costs.”
According to the authors, China appears to be the market that corrects these anomalies the fastest. And this, paradoxically, makes Shanghai futures particularly useful for building profitable trading strategies.
Where Inefficiencies Arise
To understand why this happens, we need to look at the differences between the three markets. Brent and WTI are long-standing benchmarks, extremely liquid, and monitored by thousands of traders worldwide. Shanghai futures, on the other hand, are newer, denominated in yuan, and built around a basket of Middle Eastern and Asian crudes designed to meet China’s energy needs.
These differences mean that the Chinese market is not yet perfectly aligned with Western markets. And that is precisely where opportunities for statistical arbitrage arise: a strategy that seeks to profit from temporary price deviations.
According to the authors, the phenomenon emerges with particular force during times of stress in global energy markets, such as during the pandemic or following Russia’s invasion of Ukraine. During those periods, the prices of the three benchmarks continue to move in tandem over the long term, but in the short term they can diverge enough to create trading opportunities.
The algorithm that searches for “hidden regimes”
The most innovative part of the research concerns the mathematical model used to identify these imbalances. The researchers applied a system called the Hidden Markov Model, which is also frequently used in signal analysis. Markets do not always behave in the same way. There are relatively calm phases and others dominated by sudden shocks, volatility, and geopolitical tensions.
The model therefore attempts to automatically recognize the current market “regime” and continuously update trading strategies.
“The filtering approach enables us to estimate the most likely regime and the model parameters in a dynamic way.”
In other words: the algorithm learns from market movements almost in real time. It is precisely this dynamic approach that, according to the study, yields better results than traditional strategies based solely on historical price observations.
Shanghai beats traditional benchmarks
The research analyzed over five years of data, from March 2018 to June 2023, spanning some of the most turbulent phases in recent oil history: the price collapse during the Covid pandemic, the post-pandemic recovery, and the energy crisis following the war in Ukraine.
The results show that more sophisticated strategies (those based on the predictive model) tend to generate higher returns than traditional approaches.
In the main case studied by the authors, the best strategy produced an annualized return of over 15%, with relatively low risk levels compared to a simple passive investment in oil. Even more interesting is the fact that some strategies continue to work even when traditional statistical relationships between market pairs appear to break down.
“Incorporating three futures contracts enables the implementation of arbitrage strategies even in cases where pairwise cointegration is not detected.”
In practice: using Brent, WTI, and Shanghai simultaneously allows for the identification of opportunities that elude classic “two-market” strategies.
An integration which is still incomplete
Behind the math and algorithms lies a much bigger issue: China’s growing financial weight in global energy markets. Shanghai futures were also created to reduce Asia’s dependence on Western benchmarks and strengthen the yuan’s international role in oil trading. The fact that these contracts still generate market inefficiencies suggests that the process of global financial integration remains incomplete.
It is precisely in markets that are not yet fully “mature” that the most interesting opportunities for quantitative investors tend to arise. It is no coincidence that many hedge funds specializing in algorithmic trading are increasingly turning their attention to Asian energy markets. Where fragmentation still exists, in fact, there is often room for arbitrage.
