Both financial and economics problems are more frequently being explore with Evolutionary Computation (EC) techniques. Theses methods have been proven to be a powerful tool in domains were analytic solutions are not a good alternative. Problems in real world involve complexity, noisy environments, imprecision, uncertainty and vagueness. For this reason EC techniques are needed in order to solve problems related to these areas. So far it has been successfully used for estimating econometric parameters, macroecomics models, replicating laboratory results with human subjects, searching equilibriums, studying the emergence of the representative agent and rational expectations, designing public policy, in financial engineering, risk management, portfolio optimization, industrial organization, auctions, experimental economics, financial forecasting, market simulation or agent-based computational economics among many other areas.