국면전환 GARCH 모형을 이용한 코스피 변동성 분석 = Volatility Forecasting of Korea Composite Stock Price Index with MRS-GARCH Model

다국어 초록 (Multilingual Abstract)

Volatility forecasting in financial markets is an important issue because it is directly related to the profit of return. The volatility is generally modeled as time-varying conditional heteroskedasticity. A generalized autoregressive conditional heteroskedastic (GARCH) model is often used for modeling; however, it is not suitable to reflect structural changes (such as a financial crisis or debt crisis) into the volatility. As a remedy, we introduce the Markov regime switching GARCH (MRS-GARCH) model. For the empirical example, we analyze and forecast the volatility of the daily Korea Composite Stock Price Index (KOSPI) data from January 4, 2000 to October 30, 2014. The result shows that the regime of low volatility persists with a leverage effect. We also observe that the performance of MRS-GARCH is superior to other GARCH models for in-sample fitting; in addition, it is also superior to other models for long-term forecasting in out-of-sample fitting. The MRS-GARCH model can be a good alternative to GARCH-type models because it can reflect financial market structural changes into modeling and volatility forecasting.

참고문헌 (Reference)

1 황성원, "국면전환 GARCH 모형을 이용한 변동성 구조 분석 및 예측에 관한 실증 연구" 한국증권학회 40 (40): 171-194, 2011

2 Hamilton, J. D., "Time Series Analysis" Princeton University Press 1994

3 Glosten, L. R., "Relationship between the expected value and the volatility of the nominal excess return on stocks" 48 : 1779-1801, 1993

4 Gray, S. F., "Modeling the conditional distribution of interest rates as a regime-switching process" 42 : 27-62, 1996

5 Klaassen, F., "Improving GARCH volatility forecasts with regime-switching GARCH" 27 : 363-394, 2002

6 Bollerslev, T., "Generalized autoregressive conditional heteroskedasticity" 31 : 307-327, 1986

7 Marcucci, J., "Forecasting stock market volatility with regime-switching GARCH models" 9 : 1-53, 2005

8 Nelson, D. B., "Conditional heteroskedasticity in asset returns : A new approach" 59 : 347-370, 1991

9 Engle, R. F., "Autoregressive conditional heteroskedasticity with estimates of the variance of U.K. inflation" 50 : 987-1008, 1982

10 Pagan, A. R., "Alternative models for conditional stock volatility" 45 : 267-290, 1990

11 Hamilton, J. D., "A new approach to the economic analysis of nonstationary time series and the business cycle" 57 : 357-384, 1989