Abstract
This paper presents a new approach to financial forecasting, inspired by strategies used by market traders. We demonstrate that a trading system with the relatively modest task of spotting trends in progress rather than the usual goal of spotting peaks and troughs can produce highly accurate forecasts. This is achieved by using a Genetic Algorithm to select appropriate training cases which are then fed to a trading system composed of multiple GP derived trees.
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Larkin, F., Ryan, C. (2010). Modesty Is the Best Policy: Automatic Discovery of Viable Forecasting Goals in Financial Data. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2010. Lecture Notes in Computer Science, vol 6025. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12242-2_21
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DOI: https://doi.org/10.1007/978-3-642-12242-2_21
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