Genetic Algorithms: The Next Generation

Price Pattern Using Genetic Algorithms

Download now Matlab source code
Requirements: Matlab Financial Toolbox, Matlab Genetic Algorithm and Direct Search Toolbox.

Genetic algorithms belong to a class of machine learning algorithms that have been successfully used in a number of research areas. There is a growing interest in their use in financial economics but so far there has been little formal analysis. In stock market, a technical trading rule is a popular tool for analysts and users to do their research and decide to buy or sell their shares. The key issue for the success of a trading rule is the selection of values for all parameters and their combinations. However, the range of parameters can vary in a large domain, so it is difficult for users to find the best parameter combination. By using a genetic algorithm, we can look for both the structure and the parameters of the rules at the same time. We have optimized a trading system that has been developed by Alfredo Rosa using genetic algorithms: a new, complex 16-bars trading rule has been discovered and tested on Italian FIB with brilliant results.

Index Terms: Matlab, source, code, data mining, trading system, stock market prediction, trading rule extraction, genetic algorithms, trading systems, bar chart, candlestick chart, price patterns, parameter combination.

Release 1.0 Date 2007.06.11
Major features:

• Trading system using Genetic Algorithms
• Source code for parameter optimization
• High speed
• Fully customizable code
• Easy c/c++ implementation
• Demo code (protected P-files) available for performance evaluation