Three level covered call options trading model optimized with evolutionary algorithms

Evolutionary algorithms are used in solving various financial problems. Options trading strategies are preferred among traders lately, because they have leveraged and protective transaction characteristics. In this study, an option trading strategy, Covered Call, is optimized with Genetic Algorithm and Particle Swarm Optimization by using a developed Three Layer Trading model. In the first level, the trend is found. In the second level, buy-sell signals are produced with Relative Strength Indicator (RSI) by using the trend found in the first level. The final level optimizes the parameters for the Covered Call strategy. In the first level, the search space is small and the results are found by brute force. Other two levels use genetic algorithm and particle swarm optimization to optimize the appropriate parameters. To test the developed Three Layer Trading model, four ETFs are used, which are SPY, XLE, IWM and XLF. These ETFs are trained and optimized between 2005 and 2008 and tested during 2009. The results are compared with Buy & Hold strategy and previously developed Two Layer Trading Model.