The objective of this page is to show you that getting your first G.P.F. optimization going could be as simple as 1,2,3. Selecting a fitness function. Setting up a data source 3. Volatility increases, the market topology changes, and starts responding differently to new information. All of a sudden, your favorite adaptive moving average does not adapt that well anymore, your overbought stochastic comes back to earth, and all traders have to live with a new environment, and change can sometimes be unsettling.
All traders know that there are periods of time where markets are trending, or choppy or cyclical.
Making money in trending and cyclical markets is relatively easy. 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.