On the Effect of Alpha Decay and Transaction Costs on the Multi-period Optimal Trading Strategy

TL;DR

This paper investigates multi-period trading strategies considering alpha decay and transaction costs, formulating the problem as an MDP and deriving optimal policies with convergence proofs and asymptotic analysis.

Contribution

It introduces a novel formulation of the trading problem incorporating alpha decay and transaction costs, with a new algorithm and rigorous convergence proof.

Findings

Optimal policies depend on alpha decay and transaction costs.

Proposed value iteration algorithm converges reliably.

Asymptotic analysis provides insights for small transaction costs.

Abstract

We consider the multi-period portfolio optimization problem with a single asset that can be held long or short. Due to the presence of transaction costs, maximizing the immediate reward at each period may prove detrimental, as frequent trading results in consistent negative cash outflows. To simulate alpha decay, we consider a case where not only the present value of a signal, but also past values, have predictive power. We formulate the problem as an infinite horizon Markov Decision Process and seek to characterize the optimal policy that realizes the maximum average expected reward. We propose a variant of the standard value iteration algorithm for computing the optimal policy. Establishing convergence in our setting is nontrivial, and we provide a rigorous proof. Addtionally, we compute a first-order approximation and asymptotics of the optimal policy with small transaction costs.