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被引量：51

The Comparative Research on Volatility Prediction Ability of Adjusted Realized Volatility,GARCH Model and SV Model

下载PDF

导出

摘要高频金融时间序列的分析与建模是金融计量学的一个全新的研究领域,"已实现"波动率是针对高频金融时间序列的一种全新的波动率的度量方法。为了降低"已实现"波动的测量误差,提出更有效的调整"已实现"波动。针对调整"已实现"波动的长记忆性和"杠杠"效应建立ARFIMAX模型。通过设定一系列标准,全面比较基于调整"已实现"波动的ARFIMAX模型、GARCH模型以及SV模型的预测能力。 High-frequency financial time series analysis and modeling is a new research field in financial econometrics, and (realized) volatility is a new measure approach of volatility in high-frequency data field. The paper puts forward a more (efficient) approach which is adjusted realized volatility based on realized volatility. This paper constructs ARFIMAX model (aimed) at the adjusted realized volatility's long memory characteristics and leverage effect. At last, through a variety of (criterions) the paper studies prediction ability of adjusted realized volatility, GARCH model and SV model.

作者徐正国张世英

机构地区天津大学管理学院

出处《系统工程》 CSCD 北大核心 2004年第8期60-63,共4页 Systems Engineering

基金国家自然科学基金资助项目(70171001)

关键词高频金融时间序列调整“已实现”波动率二次变差长记忆性 Mincer—Zarnowitz回归 High-frequency Financial Time Series Adjusted Realized Volatility Quadratic Variation Long Memory (Characteristics ) Mincer-zarnowitz Regression

分类号 F830 [经济管理—金融学]

引文网络
相关文献

参考文献11

1Andersen 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.
2Andersen T G,Bollerslev T,Diebold F,Labys P. The distribution of exchange rate volatility[J]. Journal of American Statistical Association,2001,96:42～55.
3Andersen T G,Bollerslev T,Diebold F,Ebens H. The distribution of stock return volatility[J]. Journal of Financial Economics,2001,61:43～76.
4Andersen T G,Bollerslev T,Diebold F,Labys P. Modelling and forecasting realized volatility[J]. Econometrica,2003, 71(2):579～625.
5Blair 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.
6Andersen T G,Bollerslev T. Answering the critics:yes, ARCH models do provide good volatility forecasts[J]. International Economic Review,1998,39(4):885～905.
7余素红,张世英.SV与GARCH模型对金融时间序列刻画能力的比较研究[J].系统工程,2002,20(5):28-33. 被引量：38
8Andersen T G,Bollerslev T,et al. Analytic evaluation of volatility forecasts[R]. 2002.
9Beran 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.
10Hull J,White A. The pring of options on assets with stochastic volatility[J]. J.Finance,1987,42:281～300.