A Hybrid Forecasting System Based on Comprehensive Feature Selection and Intelligent Optimization for Stock Price Index Forecasting

Accurate forecasts of stock indexes can not only provide reference information for investors to formulate relevant strategies but also provide effective channels for the government to regulate the market. However, due to its volatility and complexity, predicting the stock price index has always been...

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Bibliographic Details
Published in:	Mathematics (Basel) Vol. 12; no. 23; p. 3778
Main Authors:	He, Xuecheng, Wang, Jujie
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.12.2024
Subjects:	Accuracy Algorithms Analysis Data compression Efficiency Forecasting Forecasts and trends Gaussian process interval prediction Investments Machine learning Multivariate analysis Optimization Political aspects Prices and rates recursive feature elimination with cross-validation Root-mean-square errors stack autoencoder Statistical analysis Stock exchanges stock index forecasting Stock price indexes Stock prices Stocks Support vector machines Trends Variables Volatility
ISSN:	2227-7390, 2227-7390
Online Access:	Get full text
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