.NET News Desk
Timing the Market with Distributed Genetics
Taking the winning side in trades using Genetic Programming and Grid Computing
By: Derek Ferguson
May. 30, 2008 12:30 PM
Genetic programming uses a model for solving such problems that simulates biological evolution. A number of solutions are randomly generated, then tried and evaluated on the basis of how close they come to solving the problem at hand. Depending on how good or poor a given solution seems to be it will either become the starting point for additional, randomly generated solutions, or dropped from further consideration.
In evolutionary terms, this is similar to the way in which new mutations within a species prove to be beneficial, harmful, or neutral over time. A caveman with a third arm might have found that he was better-equipped for hunting. This might have made him especially popular with the cave ladies and, as a result, he had more offspring and a greater impact on succeeding generations. By way of contrast, a modern-day salesman with a third arm would probably not be as successful – constantly getting it caught in revolving doors and such – and as a result would probably die without progeny, living in the proverbial van down by the river.
The .NET Tool Kit
The Digipede Framework
Second are the Digipede Agents. You will typically install a Digipede Agent on every machine that you want to have performing work as a part of your grid computing environment. The free Developer Edition allows you to install a maximum of two Agents – enough to allow you to completely build and test a grid program, but probably not enough to leverage much benefit for many grid-worthy computing applications.
Finally, and in many ways most important, is the Digipede Framework itself. By providing just a handful of classes for extension and/or consumption, Digipede allows you to focus on writing the “business logic” you need to have running on a grid. The Digipede software will completely handle the relatively inane tasks of distributing and coordinating the tasks you need to have performed across your grid.
John Koza’s Genetic Programming Textbook
Designing the Stock Selection Application
A quick review of financial planning guides, trading websites, etc., will quickly cause you to zero in on a handful of likely data points for long-term financial analysis. For this engine, we will use the “Real Time Market Data” web service made available by WebServiceX.NET.
This web service provides a façade over the market data published by the INET electronic exchange. The operations we are interested in, specifically, are:
Reader Feedback: Page 1 of 1
SOA World Latest Stories
Subscribe to the World's Most Powerful Newsletters
Subscribe to Our Rss Feeds & Get Your SYS-CON News Live!
SYS-CON Featured Whitepapers
Most Read This Week