Empirical Analysis of Chinese Stock Market Volatility Based on GARCH Models and Markov Switching Models

DOI

10.2991/icssed-19.2019.94How to use a DOI?

Keywords

Volatility, Markov switching models, GARCH models.

Abstract

Volatility has been the focus in the financial field in recent decades. It can be used to measure the uncertainties of yield and represent the risk of assets. In this paper, GARCH models and Markov switching models are used to fit the volatility of the Chinese stock market. Results illustrate that Markov switching models take the regime-switch as an endogenous variable and a random process, which enable it to describe all the remarkable structural change in one united model and help to forecast price. Therefore, it is superior to GARCH models.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Zou Na
AU  - Zhu Jiahui
AU  - Cai Yanli
PY  - 2019/05
DA  - 2019/05
TI  - Empirical Analysis of Chinese Stock Market Volatility  Based on GARCH Models and Markov Switching Models
BT  - Proceedings of the 2019 4th International Conference on Social Sciences and Economic Development (ICSSED 2019)
PB  - Atlantis Press
SP  - 490
EP  - 497
SN  - 2352-5398
UR  - https://doi.org/10.2991/icssed-19.2019.94
DO  - 10.2991/icssed-19.2019.94
ID  - Na2019/05
ER  -