基于人工神经网络模型的沪深300指数预测

Forecast of CSI 300 Index Based on Artificial Neural Network Model

摘要: 基于当前疫情冲击经济、抑制需求，国外超级宽松货币政策频出的背景下，本文采用二层人工神经网络模型，选取了2017年7月6日至2020年4月24日共1021个沪深300指数数据为样本，进行股票市场预测。预测结果证明人工神经网络模型预测股价误差率可控，可以在短期内为股价预测提供一定借鉴和指导。

Abstract: Based on the background of the current epidemic impact on the economy and the suppression of demand, frequent foreign super loose monetary policies, this paper uses a two-layer artificial neural network model and selects a total of 1021 Shanghai and Shenzhen 300 index data from July 6, 2017 to April 24, 2020 as a sample for stock market forecasting. The prediction results prove that the artificial neural network model predicts the stock price error rate to be controllable, and can provide some reference and guidance for stock price prediction in the short term.