Genetic Algorithms, Trading Strategies and Stochastic Processes: Some New Evidence from Monte Carlo Simulations
نویسندگان
چکیده
In this paper, the performance of canonical GA-based trading strategies are evaluated under di erent time series. Two classes of time series model are considered, namely, linear ARMA model and bilinear model. Unlike many existing applications of computational intelligence in nancial engineering, for each performance criterion, we provide a rigorous asymptotic statistical test based on Monte Carlo simulation. As a result, this study provides us with a thorough understanding about the e ectiveness of canonical GAs for evolving trading strategies under these two classes of time series.
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