BP算法的改进及其在股票价格预测中的应用

为加速BP算法的收敛，提出了一种物理意义明确、体现人脑优选本质的新的激励函数，通过动态调整此激励函数的参数并结合已有的一些BP改进算法，用之进行股票价格的预测，得到了满意的结果。同时，股票价格的可预测性也从另一角度证明了我国不成熟股票市场的非有效性。只要预测模型选取恰当，可获得超过市场平均盈利水平的收益。

Improved BP Algorithm and Its Application in Prediction of Stock Price

In order to speed the convergence of BP algorithm, this paper puts forward a new stimulation function,which has an explicit physical meaning and is able to reflect the optimization essence of human beings' brains. Through dynamically adjusting the parameters of the stimulation function and combining other improved BP algorithms, the authors use the stimulation function to predict the price of a stock and get a satisfactory result. On the other hand, the predictability of stock prices also proves the noneffective of the immature stock markets of China from another angle. As long as a proper prediction model is chosen, people can get more profits than average market earnings.