Suraphan Thawornwong

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It has been widely accepted by many studies that non-linearity exists in the financial markets and that neural networks can be effectively used to uncover this relationship. Unfortunately, many of these studies fail to consider alternative forecasting techniques, the relevance of input variables, or the performance of the models when using different trading(More)
It has been widely accepted that predicting stock returns is not a simple task since many market factors are involved and their structural relationships are not perfectly linear. Recently, a promising data mining technique in machine learning has been proposed to uncover the pre-dictive relationships of numerous ÿnancial and economic variables. Inspired by(More)
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