Recorded Webinar: Using Genetic Algorithms in Financial Applications

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Genetic algorithms are useful for solving problems that are difficult to solve using traditional gradient-based optimization techniques, including problems that are not well defined or difficult to model mathematically. For example, genetic algorithms are useful for solving problems that contain multiple or mixed data types, such as complex variables, mixed integers, or user-defined data types.

In this webinar, we will demonstrate a method of selecting a subset of equities from a larger universe that best matches a desired risk-reward profile. We introduce a custom integer-based data type to encode the equities to be included in the portfolio. By creating a set of evolutionary rules specific to this data type, we will see how you can customize Genetic Algorithm and Direct Search Toolbox to the specific requirements of a sample problem. A question and answer session will follow the webinar presentation.

Product Focus

• MATLAB
• Genetic Algorithms and Direct Search Toolbox
• Optimization Toolbox
• Financial Toolbox
• Datafeed Toolbox

This webinar was recorded on 11 Dec 2007

Duration: 57 Minutes