Macroeconomic Short-Term High-Precision Combined Forecasting Algorithm Based on Grey Model

• Published in: Security and communication networks Vol. 2021; pp. 1 - 9
• Main Author: Li, Cao
• Format: Journal Article
• Language: English
• Published: London Hindawi 16.09.2021; John Wiley & Sons, Inc
• Subjects: Accuracy; Algorithms; Commodities; Consumer Price Index; Economic development; Economic factors; Economic forecasting; Economic models; Forecasting; GDP; Gross Domestic Product; Macroeconomics; Mathematical models; Neural networks; Standard deviation; System theory; China
• ISSN: 1939-0114; 1939-0122
• DOI: 10.1155/2021/7026064

Using the characteristics of grey forecasting, which requires a small amount of sample data and a simple modeling process, to predict the main macroeconomic indicators in the early stage, combined with the filtering decomposition method and the production function method, establishes a short-term high-precision combination forecasting algorithm for macroeconomics based on the grey model. The algorithm uses the improved HP filter method in the HP filter method to study whether the potential economic growth rate can be more accurately measured, and the production function method is used to calculate the potential economic growth rate. First, the two methods are used to calculate the potential economic growth rate. The accuracy of this method finally established a combined model based on the two models for short-term forecasting. Under the premise of considering economic factors, the input data is preprocessed, and the high-precision combined forecast is used to finally obtain the macroeconomic forecast results. The calculation examples in the paper show that the method is feasible and effective.