CORRELATION ANALYSIS OF FINANCIAL INDICATORS AND STOCK PRICE FLUCTUATIONS BASED ON ARTIFICIAL INTELLIGENCE SYSTEM

Abstract

The correlation analysis of financial indicators and stock price fluctuations utilizes an artificial
intelligence system. In the Generative Adversarial Networks (GANs) artificial neural network, the middle layer
contains a number of neurons equal to the training samples. Each neuron in the GANs network stores one training
sample, referred to as a direct memory artificial neuron. By adjusting connection weights, the model more precisely
approximates the nonlinear mapping of stock market price fluctuations, enabling accurate short-term predictions of
stock prices. This research introduces a novel neural network model for constructing predictive models. In
comparison to current methodologies, it demonstrates satisfactory performance[1]