Risk Measurement of China's SME Board Market Based on GARCH-VaR

DOI

10.2991/icsshe-18.2018.212How to use a DOI?

Keywords

SME board, GARCH model, VaR, Normal distribution, T distribution

Abstract

The GARCH model can describe the dynamic characteristics of the stock market yield better, but the conclusion of the analysis is not the same because of the different sample data selected by the research. On the basis of the research at home and abroad, this paper selects the China's SME board index which is more familiar to investors, selects the closing price data from June 1, 2006 to June 1, 2017, uses three different types of models, such as GARCH, EGARCH, TARCH, and so on. Under the normal distribution, the students' distribution and the GED distribution, the order of return is the order of return. The column data are fitted and the estimated results are compared and analyzed. It is found that China's SME board index has a more obvious ARCH effect, which is characterized by stationarity, non-normality, peak and thick tail. By comparing the VaR values under different GARCH models, it is found that the GARCH model under the assumption of t distribution can better reflect the risk of China's SME board market. Thus, the overall situation and risk characteristics of the income distribution in the SME board market in China are better obtained, so as to provide the appropriate risk measurement model and decision basis for the developing SME board market.

Copyright

© 2018, 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/).

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TY  - CONF
AU  - Mengnan Wang
AU  - Liang Dai
PY  - 2018/09
DA  - 2018/09
TI  - Risk Measurement of China's SME Board Market Based on GARCH-VaR
BT  - Proceedings of the 2018 4th International Conference on Social Science and Higher Education (ICSSHE 2018)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/icsshe-18.2018.212
DO  - 10.2991/icsshe-18.2018.212
ID  - Wang2018/09
ER  -