Modeling Turning Points in Financial Markets with Soft Computing Techniques
作者： Antonia Azzini , Célia da Costa Pereira , Andrea G. B. Tettamanzi
DOI: 10.1007/978-3-642-13950-5_9
关键词:
摘要: Two independent evolutionary modeling methods, based on fuzzy logic and neural networks respectively, are applied to predicting trend reversals in financial time series of the instruments S&P 500, crude oil gold, their performances compared. Both methods found give essentially same results, indicating that partially predictable.
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