Advanced SearchSearch Tips
Overnight Information E ects on Intra-Day Stoc Market Volatility
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Overnight Information E ects on Intra-Day Stoc Market Volatility
Kim, Sun-Woong; Choi, Heung-Sik;
  PDF(new window)
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 2008 to June 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.
Non-trading time information;Overnight GJR-GARCH;VKOSPI;
 Cited by
변종국, 조정일 (2003). KOSPI 200 주가지수선물 도입과 주식시장의 비대칭적 변동성, <재무관리연구>, 20, 191-212.

옥기율 (1997). 주가변동성의 비대칭적 반응에 관한 실증적 연구, <증권학회지>, 21, 295-324.

이병근, 황상원 (2008). 모델프리 내재변동성의 정보효율성에 관한 연구, <선물연구>, 16, 67-94.

최영수, 이현정 (2010). 변동성 측정방법에 따른 KOSPI 200 지수의 변동성 예측비교, <한국통계학회논문집>, 17, 293-308.

Amihud, Y. and Mendelson, H. (1991). Volatility, Effciency, and Trading: Evidence from the Japanese Stock Market, Journal of Finance, 46, 1765-1789. crossref(new window)

Bekaert, G. and Wu, G. (2000). Asymmetric volatility and risk in equity markets, Review of Financial Studies, 13, 1-42. crossref(new window)

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. crossref(new window)

Bollerslev, T. P. (1986). Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31, 307-327. crossref(new window)

Engle, R. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom in ation, Econometrica, 50, 987-1008. crossref(new window)

Engle, R. and Ng, V. (1993). Measuring and testing the impact of news on volatility, The Journal of Finance, 48, 1749-1778. crossref(new window)

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. crossref(new window)

Gallo, G. M. (2001). Modelling the impact of overnight surprises on intra-daily volatility, Australian Eco-nomic Papers, 40, 567-580. crossref(new window)

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. crossref(new window)

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. crossref(new window)

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. crossref(new window)

Kim, S. W. (2010). Negative asymmetric relationship between VKOSPI and KOSPI 200, Journal of the Korean Data Analysis Society, 12, 1761-1773.

Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach, Econometrica, 59, 347-370. crossref(new window)

Oldfeld, G. and Rogalski, R. (1980). A theory of common stock returns over trading and non-trading periods, Journal of Finance, 35, 729-751. crossref(new window)