Genetic Programming Prediction of Stock Prices

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@Article{Kaboudan:1999:GPpsp,

• author = "M. A. Kaboudan",
• title = "Genetic Programming Prediction of Stock Prices",
• journal = "Computational Economics",
• year = "2000",
• volume = "16",
• number = "3",
• pages = "207--236",
• month = dec,
• publisher = "Kluwer Academic Publishers",
• keywords = "genetic algorithms, genetic programming, evolved regression models, stock returns, financial market analysis, nonlinear systems",
• ISSN = "0927-7099",
• URL = "https://rdcu.be/c0eEg",
• DOI = "doi:10.1023/A:1008768404046",
• size = "30 pages",
• abstract = "Based on predictions of stock-prices using genetic programming (or GP), a possibly profitable trading strategy is proposed. A metric quantifying the probability that a specific timeseries is GP-predictable is presented first. It is used to show that stock prices are predictable. GP then evolves regression models that produce reasonable one-day-ahead forecasts only. This limited ability led to the development of a single day-trading strategy(SDTS) in which trading decisions are based on GP-forecasts of daily highest and lowest stock prices.SDTS executed for fifty consecutive trading days of six stocks yielded relatively high returns on investment.",

}

Genetic Programming entries for Mahmoud A Kaboudan

Citations