ACD模型的发展以及在金融中的应用被引量：7

The Development of ACD Model and Its Application in Finance

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摘要最近几年,ACD(autoregressive conditional duration)模型有了很多新的发展。本文将在介绍高频数据特点的基础上结合是市场微观结构的理论对ACD模型及其迄今为止模型的一些新的发展和ACD模型在中国的实证研究进行了较全面的总结,讨论了标准ACD模型以及ACD模型的一些扩展形式的性质和设定和现存的诊断检验方法,并提出了模型存在的问题和未来可能的研究方向。本文利用标准ACD、Log-ACDII、EXACD模型分析中国股票市场的高频交易数据。研究结果表明,中国股票市场中股票的交易久期存在集聚效应,而杠杆效应并不显著。 Recently, ACD （autoregressive conditional duration） model have many new developments. This paper will firstly introduce the characteristics of financiak high frequency data. Then it provides up-to-date survey of the main developments in ACD modeling, empirical studies in china, including the properties of the standard ACD and its extensions, exiting diag- nostic tests. And finally this paper point out the problem in using ACD model and identify possible directions for future research. This paper also uses Chinese stock market high frequency data in the standard ACD model, Log-ACDII model and EXACD model. The results present that transaction duration performs clustering effect but not obvious leverage effect in Chinese stock market.

作者郭宝生任若恩

机构地区北京航空航天大学经济管理学院

出处《系统工程》 CSCD 北大核心 2007年第10期1-10,共10页 Systems Engineering

基金国家自然科学基金重点资助项目(70531010) 创新研究群体科学基金资助项目(70521001)

关键词金融工程金融高频数据ACD模型市场微观结构 Financial High Frequency Data ACD Model Market Microstructure

分类号 F830 [经济管理—金融学]

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参考文献32

1Engle E F, Russell J R. Autoregressive conditional duration:a new model for irregularly spaced transaction data[J]. Econometrica, 1998,66 : 1127-1162.
2Engle R F, Russell J R. Analysis of high frequency data[A]. Ait-Sahalia Y,Hansen L P. Handbook of financial econometrics [C]. Elsevier Science : North Holland, 2004.
3Engel R, Dufour A. Time and the price impact of a trade[J]. J. of Fin,2000,VLX(6) ,2467-2489.
4Engle R,Rusell J. Forecasting the frequency of foreign exchange prices with autoregressive conditional duration..a new model for irregular spaced transaction data[J]. Econometrics, 1997,66 : 1127- 1162.
5Engel R, Lange J. Measuring and forecasting time varying liquitry[Z]. UCSD,1997.
6Fernandes M,Grammig J. A family of autoregressive conditional duration models[J]. Journal of Econometrics, 2006,130 : 1 - 23.
7Ghysels E, Jasiak J. GARCH for irregularly spaced financial aata : the ACD-GARCH model [J]. Studies in Nonlinear Dynamics& Econometrics, 1998,2 (4) : 133-149.
8Ghysels E, Gourieroux C, Jasiak J. Stochastic volatility duration models[A]. Olsen and associates high frequency data in Finance Ⅱ , conference proceedings[C]. 1998.
9Harris A. Statistical properties of the roll serial covariance bid/ask spread estimator[J]. J. of Fin. , 1990,45:579-590.
10Hausbronck J. The dynamics of discrete bid and ask quotes[J]. J. of Fin. ,1999,54:2109-2142.

二级参考文献86

1史美景.高频数据及市场微观结构模型[J].统计与决策,2004,20(10):155-156. 被引量：1
2[1]Andersen.T.and Bollerslev.T.,Diebold.F.And Lebys.P.,1999,The Distribution of Exchange Rate Volatility,working paper,NBER.
3[2]Andersen.T.and Bollerslev.T.,1998b,Answering The Skeptics:Yes Standard Volatility Models to Provide Accurate Forecasts,International Economic Review.39,P885～905.
4[3]Ann.N.,BAE.F.,and Chan.R.,2001,Limit Orders,Depth,and Volatility:Evidence from the Stook Exchange of Hong Kong,J.of Fin.,VLVI(2),P767～788.
5[4]Bai.X,Rusell.J.and Tiao.G,2000,Beyond Merton' s Utopian:Effects of Dependence and Non-normality on Variance Estimates Using High-Frequency Data,working paper,UC.
6[5]Bai.X,Rusell.J.and Tiao.G,2000,Kurtosis of GARCH and Stochastic Volatility Models,working paper,UC.
7[6]Bollenslev.T,2001,Financial Econometrics:past development and future challenges,J.of Econometrics,100,P41～56.
8[7]Campbell J.and Shiller.R,1998a,the Dividend-price Rational Expectations of Future Dividends and Discount Fator,Rev.of Ein Stud.,1,P357～386.
9[8]Campbell J.and Shiller.R,1998b,Stock Prices,Earnings and Expected Dividends,J.of Fin,43,P661～676.
10[9]Campbell J.,1999,Asset Price,Consumption,and The Business Cycle,In John Taylor and Richard wood ford eds:Handbook of Marcoeconomics,Vol 1,North-Holland,Amsterdasm.