However, choppy, chaotic markets, and more importantly switching markets from one topology to the other can be unnerving, as they often force the trader to review their trading strategy. To our knowledge, the only way to minimize flaws is to use simple indicators that work in all type if markets, like break-outs, and raw graphical patterns. The G.P.F. is one step ahead in facilitating the trader's job in recognizing winning patterns. Genetic algorithms, and particularly the GeneHunter software from Ward Systems here provide a fantastic framework for the development of such systems. Selecting a fitness function.
Fitness is a measure of how good an optimal solution is in solving a given problem.
It can also be seen as a optimization objective. There is a list of 8 objectives to choose from. These 2 types of optimizations should be conducted in order to build your trading strategy. Bars can be hours, days, weeks, or months according to your data format. The G.P.F. also allows for common trading parameters, like slippage, commissions, and stop losses, as these parameters will significantly influence the optimization.