Dynamic cointegrated pairs trading: Mean–variance time-consistent strategies

Cointegration is a useful econometric tool for identifying assets which share a common equilibrium. Cointegrated pairs trading is a trading strategy which attempts to take a profit when cointegrated assets depart from their equilibrium. This paper investigates the optimal dynamic trading of cointegrated assets using the classical mean–variance portfolio selection criterion. To ensure rational economic decisions, the optimal strategy is obtained over the set of time-consistent policies from which the optimization problem is enforced to obey the dynamic programming principle. We solve the optimal dynamic trading strategy in a closed-form explicit solution from a nonlinear Hamilton–Jacobi–Bellman partial differential equation. This analytical tractability enables us to prove rigorously that cointegration ensures the existence of statistical arbitrage using a dynamic time-consistent mean–variance strategy via asymptotic analysis. This provides the theoretical grounds for the market belief in cointegrated pairs trading. Comparison between time-consistent and precommitment trading strategies for cointegrated assets shows the former to be a persistent approach, whereas the latter makes it possible to generate infinite leverage once a cointegrating factor of the assets has a high mean reversion rate.