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.
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© 2000 Springer-Verlag Berlin Heidelberg
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Tsang, E.P., Li, J. (2000). Combining Ordinal Financial Predictions with Genetic Programming. In: Leung, K.S., Chan, LW., Meng, H. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents. IDEAL 2000. Lecture Notes in Computer Science, vol 1983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44491-2_77
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DOI: https://doi.org/10.1007/3-540-44491-2_77
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