Abstract
Ordinal data play an important part in financial forecasting. For example, advice from expert sources may take the form of “bullish”, “bearish” or “sluggish”, or “buy” or “do not buy”. This paper describes an application of using Genetic Programming (GP) to combine investment opinions. The aim is to combine ordinal forecast from different opinion sources in order to make better predictions. We tested our implementation, FGP (Financial Genetic Programming), on two data sets. In both cases, FGP generated more accurate rules than the individual input rules.
Cite
CITATION STYLE
Tsang, E. P. K., & Li, J. (2000). Combining Ordinal financial predictions with genetic programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1983, pp. 532–537). Springer Verlag. https://doi.org/10.1007/3-540-44491-2_77
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