Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series)
Technical analysis: the complete resource for financial market technicians
Technical analysis: the complete resource for financial market technicians
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We investigate the generalization properties of a data-mining approach to single-position day trading which uses an evolutionary algorithm to construct fuzzy predictive models of financial instruments. The models, expressed as fuzzy rule bases, take a number of popular technical indicators on day t as inputs and produce a trading signal for day t + 1 based on a dataset of past observations of which actions would have been most profitable. The approach has been applied to trading several financial instruments (large-cap stocks and indices), in order to study the horizontal, i.e., cross-market, generalization capabilities of the models.