Browse > Article
http://dx.doi.org/10.5351/KJAS.2010.23.5.823

Overnight Information E ects on Intra-Day Stoc Market Volatility  

Kim, Sun-Woong (Graduate School of Business Information Technology, Kookmin University)
Choi, Heung-Sik (Graduate School of Business Information Technology, Kookmin University)
Publication Information
The Korean Journal of Applied Statistics / v.23, no.5, 2010 , pp. 823-834 More about this Journal
Abstract
Stock markets perpetually accumulate information. During trading hours the price instantaneously reacts to new information, but accumulated overnight information reacts simultaneously on the opening price. This can create opening price uctuations. This study explores the overnight information e ects on intra-da stock market volatility. GARCH models and the VKOSPI model are provided. Empirical data includes daily opening and closing prices of the KOSPI 200 index and the VKOSPI from March $3^{rd}$ 2008 to June $22^{th}$ 2010. Empirical results show that the VKOSPI signi cantly decrease during trading time when positiv overnight information moves the Korean stock upward. This study provides useful information to investors since the Korea Exchange plans to introduce a futures market for the VKOSPI soon.
Keywords
Non-trading time information; Overnight GJR-GARCH; VKOSPI;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 French, K. and Roll, R. (1986). Stock return variances: The arrival of information and the reaction of traders, Journal of Financial Economics, 17, 5-26.   DOI   ScienceOn
2 Gallo, G. M. (2001). Modelling the impact of overnight surprises on intra-daily volatility, Australian Eco-nomic Papers, 40, 567-580.   DOI   ScienceOn
3 Gerety, M. S. and Mulherin, H. J. (1994). Price formation on stock exchanges: The evolution of trading within the day, Review of Financial Studies, 7, 609-629.   DOI   ScienceOn
4 옥기율 (1997). 주가변동성의 비대칭적 반응에 관한 실증적 연구, <증권학회지>, 21, 295-324.
5 이병근, 황상원 (2008). 모델프리 내재변동성의 정보효율성에 관한 연구, <선물연구>, 16, 67-94.
6 최영수, 이현정 (2010). 변동성 측정방법에 따른 KOSPI 200 지수의 변동성 예측비교, <한국통계학회논문집>, 17, 293-308.
7 Amihud, Y. and Mendelson, H. (1991). Volatility, Effciency, and Trading: Evidence from the Japanese Stock Market, Journal of Finance, 46, 1765-1789.   DOI
8 Bekaert, G. and Wu, G. (2000). Asymmetric volatility and risk in equity markets, Review of Financial Studies, 13, 1-42.   DOI   ScienceOn
9 Boes, M., Drost, F. and Werker, B. (2007). The impact of overnight periods on option pricing, Journal of Financial and Quantitative Analysis, 42, 517-534.   DOI   ScienceOn
10 Bollerslev, T. P. (1986). Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31, 307-327.   DOI   ScienceOn
11 Engle, R. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom in ation, Econometrica, 50, 987-1008.   DOI   ScienceOn
12 Engle, R. and Ng, V. (1993). Measuring and testing the impact of news on volatility, The Journal of Finance, 48, 1749-1778.   DOI
13 Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach, Econometrica, 59, 347-370.   DOI   ScienceOn
14 Glosten, L., Jagannathan, R. and Runke, D. (1993). Relationship between the expected value and the volatility of the nominal excess return on stocks, Journal of Finance, 48, 1779-1801.   DOI
15 Jiang, G. J. and Tian, Y. S. (2005). The model-free implied volatility and its information content, The Review of Financial Studies, 18, 1305-1342.   DOI   ScienceOn
16 Kim, S. W. (2010). Negative asymmetric relationship between VKOSPI and KOSPI 200, Journal of the Korean Data Analysis Society, 12, 1761-1773.
17 Oldfeld, G. and Rogalski, R. (1980). A theory of common stock returns over trading and non-trading periods, Journal of Finance, 35, 729-751.   DOI
18 변종국, 조정일 (2003). KOSPI 200 주가지수선물 도입과 주식시장의 비대칭적 변동성, <재무관리연구>, 20, 191-212.