Systematic jumps, heterogeneity jumps and tail characteristics

LIU Jing-yi, LI Cai-yun, JIAN Zhi-hong

Systems Engineering - Theory & Practice ›› 2015, Vol. 35 ›› Issue (1) : 49-56.

PDF(752 KB)
PDF(752 KB)
Systems Engineering - Theory & Practice ›› 2015, Vol. 35 ›› Issue (1) : 49-56. DOI: 10.12011/1000-6788(2015)1-49

Systematic jumps, heterogeneity jumps and tail characteristics

  • LIU Jing-yi1, LI Cai-yun2, JIAN Zhi-hong3
Author information +
History +

Abstract

Considering systematic jumps and heterogeneity jumps as tail events, we discuss the tail characteristics of distribution of stock return from the perspective of the extreme value theory. We use time of day (TOD) method to eliminate intraday effect of high-frequency data, apply index-stock method to decompose systematic jumps and heterogeneity jumps, and the peak over threshold (POT) method to estimate the left tail and right tail parameters. Empirical studies show that the intraday effect of A-share market possesses apparent "L" type feature. Each stock exists significant systematic and heterogeneity jumps. And the tails of two jump types are obvious thick. The times and contributions of right tail jumps are larger than left in all stocks. This suggests that the frequent appearance of jumps and jump tail characteristics are an important reason for non-normal distribution of stock return.

Key words

systematic jump / extreme value theory / time-of-day method / peak over threshold method / tail jump

Cite this article

Download Citations
LIU Jing-yi , LI Cai-yun , JIAN Zhi-hong. Systematic jumps, heterogeneity jumps and tail characteristics. Systems Engineering - Theory & Practice, 2015, 35(1): 49-56 https://doi.org/10.12011/1000-6788(2015)1-49

References

[1] Barndorff-Nielsen O E. Power and bipower variation with stochastic volatility and jumps[J]. Journal of Financial Econometrics, 2004, 1: 1-37. [2] Barndorff-Nielsen O E, Shephard N. Econometrics of testing for jumps in financial economics using bipower variation[J]. Journal of Financial Econometrics, 2006, 1: 1-30. [3] Andersen T G, Bollerselev T, Diebold F X, et al. The distribution of realized exchange rate volatility[J]. Journal of the American Statistical Association, 2001, 96: 42-55. [4] Andersen T G, Bollerselev T, Diebold F X, et al. The distribution of realized exchange stock return volatility[J]. Journal of the Financial Economics, 2001, 61: 43-76. [5] Corsi F, Pirino D, Reno R. Threshold bipower variation and the impact of jumps on volatility forecasting[J]. Journal of Econometrics, 2010, 2: 276-288. [6] Mancini C. Non-parametric threshold estimation for models with stochastic diffusion coefficient and jumps[J]. Scandinavian Journal of Statistics, 2009, 2: 270-296. [7] Bollerslev T, Law T H, Tauchen G. Risk, jumps, and diversification[J]. Journal of Econometrics, 2008, 144: 234-256. [8] Bollerslev T, Todorov V, Li S. Jump tails, extreme dependencies and the distribution of stock returns[J]. Journal of Econometrics, 2013, 172(2): 307-324. [9] 欧丽莎, 袁琛, 李汉东. 中国股票价格跳跃实证研究[J]. 管理科学学报, 2011, 14(9): 60-66. Ou Lisha, Yuan Chen, Li Handong. Empirical research on jumps in stock price in Chinese stock markets[J]. Journal of Management Sciences in China, 2011, 14(9): 60-66. [10] Liao Y, Anderson H M. Testing for co-jumps in high-frequency financial data: An approach based on first-high-low-last prices[R]. Working Paper, 2011. [11] 刘勤,顾岚. 股票日内交易数据特征和波幅的分析[J]. 统计研究, 2001, 4: 36-42. Liu Qin, Gu Lan. An analysis of the characteristics and amplitude of the stock exchange data within trading day[J]. Statistical Research, 2001, 4: 36-42. [12] 孙艳, 何建敏, 周伟. 基于UHF-EGARCH模型的股指期货市场实证研究[J]. 管理科学, 2011, 24(6): 113-120. Sun Yan, He Jianmin, Zhou Wei. Empirical research on the stock index market based on the UHF-EGARCH model[J]. Journal of Management Science, 2011, 24(6): 113-120. [13] Todorov V, Bollerslev T. Jumps and Betas: A new framework for disentangling and estimating systematic risks[J]. Journal of Econometrics, 2010, 157: 220-235. [14] Haan L, Ferreira A. Extreme value theory: An introduction[M]. Berlin, Springer-Verlag, 2006. [15] 林宇, 魏宇, 黄登仕. 基于GJR模型的EVT动态风险测度研究[J]. 系统工程学报, 2008, 23(1): 45-51. Lin Yu, Wei Yu, Huang Dengshi. Study on dynamic risk management based on GJR and EVT[J]. Journal of Systems Engineering, 2008, 23(1): 45-51. [16] Pickands J. Statistical inference using extreme order statistics[J]. Annals of Statistics, 1975, 3: 119-131. [17] Ait-Sahalia Y, Cacho-Diaz J, Laeven R J A. Modeling financial contagion using mutually exciting jump processes[R]. Working Paper, 2012.

PDF(752 KB)

426

Accesses

0

Citation

Detail

Sections
Recommended

/