Jumps in High-Frequency Data on the Chinese Stock Market
- 1 Business School, Sun Yat-sen University, Guangzhou, China
- 2 Business School, Sun Yat-sen University, Guangzhou, China
Abstract
This study adopts two nonparametric methods, the activity signature function (ASF) and ratio analysis of cojumps, to test jumps in China’s stock market. Jumps in the stock price, stock-index futures, and volatility of China Securities Index (CSI) 300 index are analyzed using data on the continuous main-contract price of the index. The findings are as follows. First, in the long run, the CSI 300 index process is a continuous process exhibiting jumps at all sampling intervals. In the short run, the index becomes a pure-jump process in times of recession while exhibiting the characteristics of a continuous or even semimartingale process in certain intervals. Second, the stock-index futures process is a continuous process with jumps at all sampling intervals and, in the short run, exhibits the characteristics of a pure-jump process every 6 months. Moreover, the volatility process generally exhibits the characteristics of pure-jump processes. Third, the CSI 300 index price process and the continuous main-contract price process of the CSI 300 stock-index futures are significantly and positively related, with jumps occurring with a time lag of less than 5 minutes; by contrast, the volatility and price processes of the index are nonsignificantly related.
- Todorov, V. and Tauchen, G. (2010) Activity Signature Functions for High-Frequency Data Analysis. Journal of Econometrics, 154, 125-138.
- Jacod, J. and Todorov, V. (2009) Testing for Common Arrivals of Jumps for Discretely Observed Multi-Dimensional Processes. Annals of Statistics, 37, 1792-1838. https://doi.org/10.1214/08-AOS624
- Liu, J. and Pan, J. (2003) Dynamic Derivative Strategies. Journal of Financial Economics, 69, 401-430.
- Bollerslev, T., Law, T. and Tauchen, G. (2008) Risk, Jumps, and Diversification. Journal of Econometrics, 144, 234-256.
- Cont, R. and Tankov, P. (2003) Financial Modelling with Jump Processes. Chapman and Hall, Boca Raton, Florida. https://doi.org/10.1201/9780203485217
- Heston, S. (1993) A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options. Review of Financial Studies, 6, 327-343. https://doi.org/10.1093/rfs/6.2.327
- Eraker, B., Johannes, M. and Polson, N. (2003) The Impact of Jumps in Volatility and Returns. Journal of Finance, 58, 1269-1300. https://doi.org/10.1111/1540-6261.00566
- Wu, L. (2011) Variance Dynamics: Joint Evidence from Options and High-Frequency Returns. Journal of Econometrics, 160, 280-287.
- Geman, H. (2003) Pure Jump Levy Processes for Asset Price Modeling. EFA 2003 Annual Conference Paper No. 590.
- Barndorff-Nielsen, O. and Shephard, N. (2001) Non-Gaussian Ornstein-Uhlenbeck-Based Models and Some of Their Uses in Financial Economics. Journal of the Royal Statistical Society Series B, 63, 167-241. https://doi.org/10.1111/1467-9868.00282
- Fama, E.F. (1965) The Behavior of Stock-Market Prices. Journal of Business, 38, 34-105. https://doi.org/10.1086/294743
- Merton, R. (1976) Option Pricing When the Underlying Stock Returns Are Discontinuous. Journal of Financial Economics, 3, 125-144.
- Duffie, D., Pan, J. and Singleton, K. (2000) Transform Analysis and Asset Pricing for Affine Jump-Diffusions. Econometrica, 68, 1343-1376. https://doi.org/10.1111/1468-0262.00164
- Nelson, D.B. (1991) Conditional Heteroskedasticity in Asset Returns: A New Approach. Econometrica, 59, 347-370. https://doi.org/10.2307/2938260
- Whaley, R.E. (1993) Derivatives on Market Volatility: Hedging Tools Long Overdue. Journal of Derivatives, 1, 71-84. https://doi.org/10.3905/jod.1993.407868