Using Genetic Algorithms for Trading Applications


In Chapter 11, we discussed the basics of genetic algorithms. In this chapter, we show how they can be used in a broad range of trading applications. We will first discuss several different applications for genetic algorithms in trading. Next, we will overview the steps involved in developing a solution using a genetic algorithm. Finally, we will show how to develop a real trading system by evolving rules based on both technical and intermarket analysis.


Genetic algorithms have many uses in developing trading applications. Some of these are listed in Table 20.1.

Let's now overview how genetic algorithms are used in each of these applications.

Genetic Algorithms and Neural Networks

Genetic algorithms are useful in evolving neural networks. This application is actually two different types of applications. The first is to evolve inputs and/or the configuration of a network. Genetic algorithms can find near optimal solutions for what are called NP Complete-type problems. NP Complete means that the problem is so complex that the time required to solve it cannot be determined using a polynomial. These are problems in which the number of combinations makes it impossible to try all of them in our lifetime. Genetic algorithms can intelligently search subsets of these solutions to find a near optimal ...

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