Information and Trading Targets in a Dynamic Market Equilibrium

TL;DR

This paper models the interaction between informed trading and target-driven rebalancing in a multi-period market, deriving equilibrium strategies and analyzing how information asymmetry affects trading behavior.

Contribution

It introduces a linear Bayesian Nash equilibrium framework for a multi-period market with both an informed insider and a rebalancer with trading targets, including cases with partial and no information.

Findings

Equilibrium strategies depend on information asymmetry and trading targets.

Numerical analysis reveals how information and targets influence market dynamics.

Algorithm for computing equilibria enhances understanding of multi-period trading interactions.

Abstract

This paper investigates the equilibrium interactions between trading targets and private information in a multi-period Kyle (1985) market. There are two investors who each follow dynamic trading strategies: A strategic portfolio rebalancer who engages in order splitting to reach a cumulative trading target and an unconstrained strategic insider who trades on long-lived information. We consider cases in which the constrained rebalancer is partially informed as well as the special case in which the rebalancer is ex ante uninformed. We derive a linear Bayesian Nash equilibrium, describe an algorithm for computing such equilibria, and present numerical results on properties of these equilibria.