Optimal execution and speculation with trade signals

Abstract We propose a price impact model where changes in prices are purely driven by the order flow in the market. The stochastic price impact of market orders and the arrival rates of limit and market orders are functions of the market liquidity process which reflects the balance of the demand and supply of liquidity. Limit and market orders mutually excite each other so that the liquidity is mean-reverting. We use the theory of Meyer $\sigma $ σ -fields to introduce a short-term signal process from which a trader learns about imminent changes in order flow. Her trades impact the market through the same mechanism as other orders. With a novel version of Marcus-type SDEs, we efficiently describe the intricate timing of market dynamics at moments when her orders coincide with orders issued by others. In this setting, we examine an optimal execution problem and derive the Hamilton–Jacobi–Bellman (HJB) equation for the value function of the trader. The HJB equation is solved numerically, and we illustrate how the trader uses the signals to enhance the performance of execution problems and to execute speculative strategies.