Traditional quantitative forecasting methods based on mathematical statistical basis in the stock market to predict the effect is not very significant with, while the dft has self-organization, adaptive and other features, can automatically from historical data, extract relevant financial activities

In mathematics and statistics building based on the traditional quantitative forecasting methods in the study of the stock market forecast results are not very significant, and self-organizing, DFT has unique characteristics, such as self-adaptation can be automatically extracted from the historical

The establishment in the mathematical statistic foundation the traditional quota forecast the method in to stock market's research in forecast the effect is not very remarkable, but DFT has from the organization, auto-adapted and so on the characteristics, can automatically withdraw in the related f

Built on a foundation of mathematical statistics in traditional quantitative forecasting method in the study of stock market prediction results is not very impressive, DFT have self-organized, Adaptive characteristics, can be automatically extracted from the historical data relating to financial act

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