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Stock yield forecast has been an important issue and difficult task for both shareholders and financial professionals. In this paper, we introduce least square support vector machine (LS-SVM), an improved algorithm that regresses faster than standard SVM, and the parameters of model proposed are gained in the three levels of Bayesian inference. The work of this paper is as following: First, forecast...
Stock index forecast is not an easy job as it is subject to influence of various factors. Since 1980s, many researchers have used Back Propagation Neural Network BPNN to forecast stock price fluctuations. However, there are some limitations with BPNN. With slow convergent speed and low learning efficiency, BP learning algorithm is easy to get in local minimum and is far from being perfect in stock...
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