In today's economic globalisation and financial integration, the stock market has become increasingly complex, showing many deviations from classical financial analysis, but at the same time, some classic financial statistics have striking similarities. This shows that although the stock market is complicated, there are universal rules, and the operating rules behind it can be found through data mining. This paper mainly studies the stock price forecast analysis based on artificial neural network(NN). This paper first analyzes the artificial NN, analyzes and establishes the BP NN prediction steps, using N-R-1 three-layer network structure to construct the BP NN stock architecture prediction model. Through model verification and experimental analysis results, we can know that this paper provides some reference value in data selection, data processing and feature extraction in the research of model stock price trend prediction. It has certain practical significance to predict the price trend of the weighted stock and assist the trading decision.

Jing Zou. Stock Price Forecast Analysis Based on Artificial Neural Network. International Journal of Neural Network (2021), Vol. 2, Issue 1: 20-26. https://doi.org/10.38007/NN.2021.020103.

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