Statistical Forecasting Model of Financial Data based on Artificial Neural Network Algorithm

Abstract

With the increasing frequency of transaction data collection in the financial market, high-frequency financial data with nonlinear, non-stationary and high noise has attracted the attention of many scholars. The short-term prediction of high-frequency financial data has become a research hotspot in recent years. This paper mainly studies the statistical prediction model of financial data based on artificial neural network(NN) algorithm. Firstly, this paper discusses the classification of artificial NN, analyzes the structure of feedforward NN, constructs a statistical prediction model of financial data based on LSTM NN algorithm, and uses LSTM model to simulate the stock market data. The experimental results show that the LSTM prediction model constructed in this paper has a better fitting effect than the traditional prediction model, and can effectively predict the financial secretary statistics.