Transaction-Cost-Conscious Pairs Trading via Approximate Dynamic Programming Undergraduate
In this paper, we develop an algorithm that optimizes logarithmic utility in pairs trading. We assume price processes for two assets, with transaction cost linear with respect to the rate of change in portfolio weights. We then solve the optimization problem via a linear programming approach to approximate dynamic programming. Our simulation results show that when asset price volatility and transaction cost are sufficiently high, our ADP strategy offers significant benefits over the chosen baseline strategy. Our baseline strategy is an optimized version of a pairs trading heuristic studied in the literature [3].