Browse > Article
http://dx.doi.org/10.5351/KJAS.2011.24.1.071

An Empirical Analysis of KOSPI Volatility Using GARCH-ARJI Model  

Kim, Woo-Hwan (Department of Economics, Yonsei University)
Publication Information
The Korean Journal of Applied Statistics / v.24, no.1, 2011 , pp. 71-81 More about this Journal
Abstract
In this paper, we systematically analyzed the variation of KOSPI returns using a GARCH-ARJI(auto regressive jump intensity) model. This model is possibly to capture time varying volatility as well as time varying conditional jump intensity. Thus, we can decompose return volatility into usual variation explained by the GARCH model and unusual variation that resulted from external news or shocks. We found that the jump intensity implied on KOSPI return series clearly shows time varying. We also found that conditional volatility due to jump is generally smaller than that resulted from usual variation. We also analyzed the effect of 9.11 and the 2008 financial crisis on the volatility of KOSPI returns and conclude that there is strong and persistent impact on the KOSPI from the 2008 financial crisis.
Keywords
GARCH-ARJI; jump intensity; conditional volatility;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Andersen, T. G. (1996). Return volatility and trading volume: An information ow interpretation of stochastic volatility, Journal of Finance, 51, 169-204.   DOI
2 Andersen, T. G., Benzoni, L. and Lund, J. (2002). An empirical investigation of continuous-time equity return models, Journal of Finance, 62, 1239-1284.
3 Bates, D. S. (2000). Post-'87 crash fears in the S&P 500 futures option market, Journal of Econometrics, 94, 181-238.   DOI   ScienceOn
4 Black, F. and Scholes, M. (1973). The pricing of options and corporate liabilities, Journal of Political Economy, 81, 637-654.   DOI   ScienceOn
5 Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31, 307-327.   DOI   ScienceOn
6 Chan, W. H. and Maheu, J. M. (2002). Conditional jump dynamics in stock market returns, Journal of Business & Economic Statistics, 20, 377-389.   DOI   ScienceOn
7 Chernov, M. A., Gallant, R., Ghysels, E. and Tauchen, G. (2003). Alternative models for stock price dynamics, Journal of Econometrics, 116, 225-257.   DOI   ScienceOn
8 Maheu, J. M. and Mccurdy, T. H. (2004). News Arrival, Jump Dynamics, and Volatility Components for Individual Stock Returns, Journal of Finance, American Finance Association, 59, 755-793, 04   DOI   ScienceOn
9 Pan, J. (2002). The jump-risk premia implicit in options: Evidence from an integrated time-series study, Journal of Financial Economics, 63, 3-50.   DOI   ScienceOn
10 Ross, S. A. (1989). Information and volatility: The no-arbitrage martingale approach to timing and resolution irrelevancy, Journal of Finance, 44, 1-17.   DOI
11 구본일, 엄영호, 최완수 (2002). 비대칭 변동성 추정모형의 새로운 대안: Spline-(E)GARCH Model, <재무연구>, 15, 109-149.
12 장국현, (1999). 한국주식시장의 변동성 다이나믹스와 시간가변적 상관관계에 관한 연구, <재무연구>, 12, 315-340.
13 김우환, 김주현, 이지윤 (2010). GARCH-ARJI 모형을 활용한 금융산업의 시스템 리스크에 관한 연구, <금융안정연구>, 11, 167-187.