GP forecasts of stock prices for profitable trading

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InCollection{maboudan:2002:ECEF,

• author = "M. Kaboudan",
• title = "GP forecasts of stock prices for profitable trading",
• booktitle = "Evolutionary Computation in Economics and Finance",
• publisher = "Physica Verlag",
• year = "2002",
• editor = "Shu-Heng Chen",
• volume = "100",
• series = "Studies in Fuzziness and Soft Computing",
• chapter = "19",
• pages = "359--381",
• month = "2002",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-7908-1476-8",
• DOI = "doi:10.1007/978-3-7908-1784-3_19",
• abstract = "This chapter documents how GP forecasting of stock prices used to execute a single-day-trading-strategy (or SDTS) improves trading returns. The strategy mandates holding no positions overnight to minimise risk and daily trading decisions are based on forecasts of daily high and low stock prices. For comparison, two methods produce the price forecasts. Genetically evolved models produce one. The other is a naive forecast where today's actual price is used as tomorrow's forecast. Trading decisions tested on a small sample of four stocks over a period of twenty days produced higher returns for decisions based on the GP price forecasts.",

}

Genetic Programming entries for Mahmoud A Kaboudan

Citations