Speculative dynamics

Abstract

We develop a method for solving for equilibrium outcomes in stationary strategic settings in which speculators are informationally large and understand how their actions affect the information content of prices. This allows us to characterize speculation by institutional investors who receive private long-lived information on a recurring basis, and trade strategically. When the underlying asset value process has a stationary autoregressive structure, we develop a contraction mapping argument to solve for the stationary linear equilibrium. We derive analytically and numerically how the characteristics of private information—its quantity, persistence and correlation, and division among speculators—affect trading profits, pricing and trading strategies. Our central finding is that what matters for equilibrium outcomes are the most recent signals that speculators receive. Speculators trade so much more aggressively on new information than old that the bulk of their profits come from their two or three most recent private signals. Trading on past prices drops off faster yet; effectively only the most recent price matters.