关键词: 股票预测, AR-GARCH模型, Laguerre正交基神经网络, L-M算法

Abstract: To realize the short-term prediction of stock prices, we establish a general and concise prediction model based on Laguerre orthogonal basis neural network model (LOBNN). This paper first corrects the weight solving algorithm of the original model, and then adds a new iterative algorithm to the original algorithm (New LOBNN model). In the second step, we use the ar-garch model to pre-process the original data and obtain some corresponding data results. Finally, the final prediction model is obtained by constructing weights of different models and combining them. In order to verify the effect of the algorithm, in the experimental part, this paper uses the improved model to calculate the real data and compares the prediction accuracy of the improved LOBNN & AR-GARCH model with the previous model. The final result proves that the model not only improves the prediction accuracy, but also shows the effectiveness of the improved model in actual scenes.

Key words: stock price prediction, AR-GARCHmodel, the laguerre orthogonal basis neural network, L-M algorithm