中国股市已实现波动率的跳跃行为研究被引量：49

An Empirical Research on Jump Behavior of Realized Volatility in Chinese Stock Markets

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摘要以二次幂变差的测量为理论基础,研究了上证综指已实现波动率中的跳跃行为。将已实现波动率分解为连续样本路径方差和离散跳跃方差,研究了跳跃方差序列的统计特征,并且应用HAR-RV-C J模型对上证综指的已实现波动率进行预测。研究结果发现,几乎所有日、周和月已实现波动率的可预测性都来自连续样本路径方差,表明二次变差中的连续样本路径成分是中国股市已实现波动率预报的决定因素。 Building on theoretical results for bi-power variation measures, the jump behavior of realized volatility for Shanghai synthesized index is examined. Realized volatility is divided into two parts： the continuous sample path variation and the discontinuous jump variation. The statistical feature of jump variation is studied. The realized volatility of shanghai synthesized index is predicted by using a HAR-RV-CJ volatility forecasting model. We find that almost all of the predictability in daily, weekly, and monthly realized volatility comes from continuous sample path variation, which indicates that non-jump

作者王春峰姚宁房振明李晔

机构地区天津大学管理学院

出处《系统工程》 CSCD 北大核心 2008年第2期1-6,共6页 Systems Engineering

基金国家自然科学基金资助项目(70771076) 国家杰出青年科学基金资助项目(70225002)

关键词跳跃过程已实现波动率二次幂变差市场微观结构噪音 Jump Process Realized Volatility Bi-power Variation Market Microstructure Noise

分类号 F830 [经济管理—金融学]

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参考文献14

1Merton R C. On estimating the expected return on the market :an exploratory investigation[J]. Journal of Financial Economics, 1980,8 : 323-361.
2Nelson D B. Filtering and forecasting with misspecifled ARCH models Ⅰ:Getting the right variance with the wrong model[J]. Journal of Econometrics, 1992, 52:61-90.
3Andersen T G,Eollerslev T. Answering the skeptics: "Yes, standard volatility models do provide accurate forecasts" [J]. International Economic Review, 1998, 39:885-905.
4Andersen T G, Bollerslev T, Diebold F X, Labys P. The distribution of realized exchange rate volatility [J]. Journal of the American Statistical Association, 2001,96:42-55.
5Barndorff-Nielsen O E, Shephard N. Econometric analysis of realised volatility and its use in estimating stochastic volatility models[J]. Journal of the Royal Statistical Society, 2002,64 : 253-280.
6Barndorff-Nielsen O E, Shephard N. Estimating quadratic variation using realized variance[J]. Journal of Applied Econometrics, 2002,17:457-478.
7Meddahi N. A theoretical comparison between integrated and realized volatility [J]. Journal of Applied Econometrics, 2002,17:479-508.
8Andersen T G, Bollerslev T, Diebold F X, Labys P. Modeling and forecasting realized volatility [J]. Econometrica, 2003,71 : 579-625.
9Barndorff-Nielsen O E, Shephard N. Power and bipower variation with stochastic volatility and jumps [J]. Journal of Financial Econometrics, 2004,2 : 1 37.
10Barndorff-Nielsen O E, Shephard N. Econometrics of testing for jumps in financial economics using bipower variation [J]. Journal of Financial Econometrics,2005,4:1-30.

二级参考文献26

1徐正国,张世英.调整"已实现"波动率与GARCH及SV模型对波动的预测能力的比较研究[J].系统工程,2004,22(8):60-63. 被引量：52
2徐正国,张世英.高频时间序列的改进“已实现”波动特性与建模[J].系统工程学报,2005,20(4):344-350. 被引量：18
3Andersen T G,Bollerslev T,Diebold F,Labys P. Exchange rate returns standardized by realized volatility are (nearly) Gaussian[J]. Multinational Finance Journal,2000,4:159～179.
4Andersen T G,Bollerslev T,Diebold F,Labys P. The distribution of exchange rate volatility[J]. Journal of American Statistical Association,2001,96:42～55.
5Andersen T G,Bollerslev T,Diebold F,Ebens H. The distribution of stock return volatility[J]. Journal of Financial Economics,2001,61:43～76.
6Andersen T G,Bollerslev T,Diebold F,Labys P. Modelling and forecasting realized volatility[J]. Econometrica,2003, 71(2):579～625.
7Blair B J,Poon S H,Tarlor S J. Forecasting S&P 100 volatility:the incremental information content of implied volatilities and high frequency index returns[J]. Journal of Econometrics,2001,105:5～26.
8Andersen T G,Bollerslev T. Answering the critics:yes, ARCH models do provide good volatility forecasts[J]. International Economic Review,1998,39(4):885～905.
9Andersen T G,Bollerslev T,et al. Analytic evaluation of volatility forecasts[R]. 2002.
10Beran J. Maximum likelihood estimation of the differencing parameter for invertible and short and long memory autoregressive integrated moving average models[J]. Journal of the Royal Statistical Society,1995,57(4):659～672.