统计与决策2025，Vol.41Issue(22)：17-23,7.DOI:10.13546/j.cnki.tjyjc.2025.22.003
考虑相依结构的金融高频数据函数型分类预测方法
Functional Classification Prediction Method for Financial High-frequency Data with Consideration of the Interdependency Structure
摘要
Abstract
Intraday financial high-frequency data can be regarded as a continuous function,and there is often interdepen-dency among the resulting function series.In order to improve the accuracy and robustness of forecasting,this paper proposes a classification-based mixed expectation forecasting method(cDFPC),which takes into account the intraday volatility patterns and daily interdependency structure of high-frequency financial data.Firstly,the potential volatility pattern categories of intraday fi-nancial high-frequency data are identified based on functional adaptive clustering analysis,and the functional discriminant crite-rion for volatility pattern category attribution is constructed.Secondly,the long-term covariance operator is reconstructed to cor-rect the covariance of the dependent function series,and the parameter estimation of the interdependency function-type regression model is given.Finally,the values of the predicted objects in each category are predicted based on the interdependency func-tion-type regression model;the posterior probabilities of their category affiliation are calculated by using the functional discrimi-nant model,and the predicted values of each category are aggregated with this weight.The numerical simulation results show that the mixed expectation forecasts considering volatility patterns can improve the forecasting accuracy,and that cDFPC has advantag-es in forecasting both long-term and short-term interdependency function data.The empirical evidence based on the opening price forecast of the Shanghai Stock Exchange Composite Index finds that the intraday volatility pattern and daily interdependency structure are significantly present,and that the relative forecasting advantage of cDFPC remains robust.关键词
波动模式/相依结构/自适应分类/混合期望/函数型时间序列Key words
fluctuation patterns/interdependent structure/adaptive classification/mixed expectation/functional time series分类
管理科学引用本文复制引用
徐妍,郭梦霞..考虑相依结构的金融高频数据函数型分类预测方法[J].统计与决策,2025,41(22):17-23,7.基金项目
江苏省社会科学基金青年项目(25ZHC024) （25ZHC024）
