Abstract
This paper describes an application of genetic programming to forecasting financial markets that allowed the authors to rank first in a competition organized within the CEC2000 on “Dow Jones Prediction”. The approach is substantially driven by the rules of that competition, and is characterized by individuals being made up of multiple GP expressions and specific genetic operators. © Springer-Verlag Berlin Heidelberg 2001.
Cite
CITATION STYLE
Santini, M., & Tettamanzi, A. (2001). Genetic programming for financial time series prediction. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2038, 361–370. https://doi.org/10.1007/3-540-45355-5_29
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