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The challenge of stock forecasting is appealing
because a small forecasting improvement can increase profit
significantly. However, the volatile nature of the stock market
makes it difficult to apply linear models, simple time-series or
regression techniques. Consequently, support vector machine
(SVM) has become a good alternative. It is a popular tool in
time series forecasting for the capital investment industry. This
machine learning technique which is based on a discriminative
classifier algorithm, forecasts more accurately the financial