Title of article :
Genetic Programming Prediction of Stock Prices
Author/Authors :
Kaboudan، M. A. نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2000
Pages :
-206
From page :
207
To page :
0
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 time series 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.
Keywords :
Diel variation , Phragmites australis , Typha latifolia , Boreal lake , Vesij?rvi , Methane emission
Journal title :
COMPUTATIONAL ECONOMICS
Serial Year :
2000
Journal title :
COMPUTATIONAL ECONOMICS
Record number :
19240
Link To Document :
بازگشت