Prediction of High-Frequency Economic Data Based on Stochastic Fluctuation Model

Year: 2022

Type: article

Abstract: In order to improve the effect of economic high-frequency data analysis, this paper combines the stochastic fluctuation model to carry out the forecast analysis of economic high-frequency data. Moreover, this paper uses the spider web model for data processing and makes a preliminary judgment on the extent to which futures/stock prices lead the spot through error correction model, impulse response, and variance decomposition. Furthermore, this paper studies the contribution of futures/stock price changes to the effective price through the common factor model so as to obtain its price discovery efficiency. In addition, this paper judges the efficiency of price discovery by studying the contribution of futures/stock price changes to the effective price. Finally, based on the research idea of futures/stock price discovery efficiency, an intelligent data analysis model is constructed. The experimental study shows that the economic high-frequency data prediction model based on the stochastic fluctuation model proposed in this paper has a good effect on the analysis and prediction of economic high-frequency data.

Source: Security and Communication Networks

DOI: 10.1155/2022/4109563

Authors: Xiaoyang Zhang, Tianxiang Qi, Dong-Joo Kim

Institution: Woosuk University

Language: English

Topic: Stock Market Forecasting Methods

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $2,670

OpenAlex ID: W4280488306