桂林理工大学学报2024，Vol.44Issue(1)：168-174,7.DOI:10.3969/j.issn.1674-9057.2024.01.024
基于QR-MS(2)-EGARCH(1,1)-st模型的互联网金融指数风险度量
Risk measurement of internet finance index based on QR-MS(2)-EGARCH(1,1)-st model
摘要
Abstract
Based on the daily closing price data of the internet finance index from 2012 to 2021,the two-zone MS-GARCH(1,1)model is firstly used to describe the fluctuation process of the internet finance index,and the optimal model MS(2)-EGARCH(1,1)-st is selected through analysis.The results show that the return rate of the internet finance index has two clearly divided states:the mild fluctuation state is more persistent than the shape fluctuation state,and the shape fluctuation state has asymmetric effects.Secondly,the combined model of MS-EGARCH model and quantile regression(QR)model are used to measure the risk of internet finance return series,and the success rate is calculated by Kupiec backtracking test method.The results show that the success rate of value at risk(VaR)obtained by QR-MS(2)-EGARCH(1,1)-st is higher.关键词
互联网金融/状态转换/QR-MS-EGARCH/VaRKey words
internet finance/state transistion/QR-MS-EGARCH/VaR分类
管理科学引用本文复制引用
蒋文希,唐国强,甘柳燕..基于QR-MS(2)-EGARCH(1,1)-st模型的互联网金融指数风险度量[J].桂林理工大学学报,2024,44(1):168-174,7.基金项目
国家自然科学基金项目(71963008) （71963008）
