The Professional Trader has features to optimize the inputs to nets. There have been others who have used Genetic Algorithms (GAs) to find inputs to feed a net before, but we are also finding optimum parameters for the indicators you are using, as well as the buy/sell thresholds when training by profit. There are several objective functions for optimization, not just simple profit.
The most exciting thing about the Professional Trader may not have anything to do with neural nets. The most exciting thing may be the trading strategy optimizer, which optimizes systems by GA even if they don't have neural nets! For example, you can enter a traditional trading strategy (using crossovers and breakouts, say) and then find optimal parameters for those crossovers and breakouts. Not only that, but you can tell the optimizer to get rid of useless rules if you have provided several. We have actually built some pretty good trading systems that didn't use nets at all.
Optimizer
The NeuroShell Trader Professional includes a trading strategy optimizer, which optimizes systems by genetic algorithm even if they don't have neural nets! For example, you can enter a traditional trading strategy (using crossovers and breakouts, say) and then find optimal parameters for those crossovers and breakouts. Not only that, but you can tell the optimizer to get rid of useless rules if you have provided several. We have actually built some pretty good trading systems that didn't use nets at all. To learn more about trading strategies, visit the
The Trader Professional also has features to optimize the inputs to nets. There have been others who have used genetic algorithms to find inputs to feed a net before, but the NeuroShell Trader Professional can also find optimum parameters for the indicators as well as the buy/sell thresholds when training by profit.
How Are Genetic Algorithms Different than Other Optimizers?
Most optimization techniques used today are simple "exhaustive search" methods, meaning that every possible combination is tried to see what was the best one. This is a very accurate approach, since you are bound to find the best combination of variables - eventually. However, it is a very inefficient approach, because whenever there are more than a few thousand combinations, it takes too long to try them all. That is why users of exhaustive search optimizers tend to limit the number of variables they use, or tend to limit the number of values these variables can take.
The genetic algorithm, by contrast, does not try every possible combination. It attempts instead to intelligently get closer and closer to the best solution. Therefore, far more variables can be utilized, and you can allow all values of a variable. Optimization can still take a good deal of time if you give a GA a fair number of variables, but it will be doing much more work in that amount of time.
More efficient optimizers than exhaustive search optimizers are in use. If they are not genetic algorithms, however, they are most likely only searching one section of the search space at a time. Genetic algorithms are searching dozens or hundreds of parts of the search space simultaneously. This means they are far less susceptible to becoming stuck in "local minima" as the others quite often do. (Local minima are decent solutions that the optimizer can never “get out of” in order to find better solutions.)
Custom Indicators
Indicators you build can now be saved and used later in different charts. Saved indicators can also be loaded into the regular Trader, meaning that you can now sell or distribute indicators to all NeuroShell Trader users. You can save them in existing indicator categories, or invent your own.
