A continuous time approximation of an evolutionary stock market model
We derive a continuous time approximation of the evolutionary market selection model of Blume & Easley (1992). Conditions on the payoff structure of the assets are identified that guarantee convergence. We show that the continuous time approximation equals the solution of an integral equation in a random environment. For constant asset returns, the integral equation reduces to an autonomous ordinary differential equation. We analyze its long-run asymptotic behavior using techniques related to Lyapunov functions, and compare our results to the benchmark of profit-maximizing investors.
Portfolio theory, evolutionary finance, continuous time Euler approximation, stochastic processes in random environments, Lyapunov function