A measure of the dynamics of an attractor. Each dimension has a Lyapunov exponent. A positive exponent measures sensitive dependence on initial conditions, or how much our forecasts can diverge based upon different estimates of starting conditions. Another way to view Lyapunov exponents is the loss of predictive ability as we look forward into time. Strange Attractors are characterized by at least one positive exponent. A negative exponent measures how points converge towards one another. Point Attractors are characterized by all negative variables. See: Attractor, Limit Cycle, Point Attractor, Strange Attractor.
Copyright © 2011 Campbell R. Harvey, Professor of Finance, Fuqua School of Business at Duke University