Examined are the most frequent mistakes that lead the first-time programmers to creation of a "super-moneymaking" (when tested) trading systems. Exemplary experts that show fantastic results in tester, but result in losses during real trading are presented.
Genetic (evolutionary) algorithms are used for optimization purposes. An example of such purpose can be neuronet learning, i.e., selection of such weight values that allow reaching the minimum error. At this, the genetic algorithm is based on the random search method.
Many programs of technical analysis allow to test trading strategies on history data. In the most cases, the testing is conducted on already completed data without any attempts to model the trends within a price bar. It was made quickly, but not precisely