Forecasting the realized volatility based on jump, jump intensity and regime switching in stock market

被引：0
|
作者：
Ma F. [1 ]
Wang J. [1 ]
Guo Y. [1 ]
Lu F. [1 ]
机构：
[1] School of Economics and Management, Southwest Jiaotong University, Chengdu
来源：
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2023年 / 43卷 / 02期
基金：
中国国家自然科学基金;
关键词：
heterogeneous autoregressive; jump; jump intensity; Markov regime-switching; volatility predictability;
D O I：
10.12011/SETP2022-1606
中图分类号：
学科分类号：
摘要：
This paper constructs a series of new volatility prediction models by introducing the jump and jump intensity to the heterogeneous autoregressive (HAR) model and together considering a Markov regime switching model with a fixed transition probability matrix. To evaluate the predictability of the above prediction models on Chinese stock market volatility, popular statistical tests such as the model confidence set (MCS), out-of-sample R2 test and direction-of-change test are used. The empirical results indicate that: 1) compared with the benchmark, the regressions incorporate the regime switching can achieve superior forecasting performance; 2) the forecasting model with jump component, jump intensity and regime switching can outperform peers; 3) the MS-HAR-TJI model still can successfully predict the stock realized volatility during the COVID-19 and high volatility periods. © 2023 Systems Engineering Society of China. All rights reserved.
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收藏
页码：371 / 382
页数：11
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