金融波动研究的新进展及未来展望被引量：3

Theory on Financial Volatility:New Development and Prospects

下载PDF

导出

摘要金融波动的学术研究已经取得了突破性的进展,并且成为金融计量学中相对独立、颇具特色和最为活跃的研究领域之一。首先介绍了变结构金融波动模型研究取得的新进展,Copula函数在金融波动分析中的应用,Copula函数在金融波动相关性分析和金融传染分析中取得的新进展,以及基于高频数据的金融波动研究近年来取得的新进展,最后对金融波动研究领域中未来值得研究的方向进行了展望。　Study on financial volatility has become an independent and active research field in econometrics.Firstly,this paper reviews the new developments in structural change volatility models.Secondly,it introduces the new developments of copula which is applied to study on financial volatility,mainly the application of copula in analysis of correlations of financial volatility and spillovers of financial volatility.Thirdly,it introduces the study on financial volatility based on high frequency data.In addition,this paper prospects the new research field in the study on financial volatility.

作者霍光耀郭名媛

机构地区天津城市建设学院天津大学管理学院

出处《西北农林科技大学学报（社会科学版）》 2007年第5期49-55,共7页 Journal of Northwest A&F University(Social Science Edition)

基金国家自然科学基金资助项目(70471050)

关键词金融波动变结构 COPULA函数 (超)高频数据 financial volatility structural change copula high frequency data

分类号 F830 [经济管理—金融学]

引文网络
相关文献

参考文献40

1CHEN G M,KWOK C Y,Rui O M.The day-of-the-week regularity in the stock markets of China[J].Journal of Multinational Financial Management,2001 (11):139-163.
2NAKATSUMA.Structual changes in volatility of foreign exchange rates after the Asian financial crisis[J].Asia-Pacific Financial Markets,2000(7):69-82.
3HAMILTON J D,SUSMEL R.Autoregressive conditional heteroskedasticity and changes in regime[J].Journal of Econometrics,1994 (64):307-333.
4HAMILTON J D,SUSMEL R.Autoregressive conditional heteroskedasticity and changes in regime[J].Journal of Econometrics,1994(64):307-333.
5CAI.A markov model of switching-regime ARCH[J].Journal of Business and Economic Statistics,1994(12):309-316.
6SO M K P,K LAM,W K LI.A stochastic volatility model with Markov-switching[J].Journal of Business,Economic Statistics,1998(16):244-253.
7SMITH D R.Markov-switching stochastic volatility diffusion models of short term interest rates,working papers,2000.
8KALIMIPALLI.SUSMEL.Regime-switching stochastic volatility and short-term interest rates[J].working papers,2002.
9NELSEN R B.An introduction to copulas[M].New York:Springer,1998.
10ROCKINGER M,JONDEAU E.Conditional dependency of financial series:an application of copulas[Z].Working Paper of Department of Finance,HEC School of Management,Paris,2001.

二级参考文献45

1[1]Nelsen, R. B (1998), An Introduction to Copulas, Lectures Notes in Statistics, 139,Springer Verlag, New York.
2[2]Embrechts, P., Lindskog, F. And McNeil, A. (2001), Modelling Dependence with Copulas and Applications to Risk Management. Dept. of Math. CH-8092, Zürich, Switzerland.
3[3]Bouyé, E. (2000), Copulas for Finance, A Reading Guide and Some Applications. City University Business School,London.
4[10]Sklar A. Fonctions de repartition àn dimensions et leurs marges[J]. Publication de 1' Institut de Statistique de 1' Université de Paris, 1959, 8: 229-231.
5[11]Nelsen R B. An Introduction to Copulas[M]. New York: Springer, 1998.
6[12]Frees E W, Valdez E A. Understanding relationships using copulas[J]. North American Actuarial Journal, 1998, 2 (1): 1-25.
7[13]Bouyé E, Durrleman V, Nikeghbali A, et al. Copulas for Finance: A Reading Guide and Some Applications[ R]. London: Financial Econometrics Research Centre, City University Business School, 2000.
8[14]Patton A J. Estimation of Copula models for Time Series of Possibly Different Lengths[ R ]. San Diego: Department of Economics,University of California, 2001.
9[15]Diebold F X, Gunther T, Tay A S. Evaluating density forecasts with applications to financial risk management[J]. International Economic Review, 1998, 39: 863-883.
10[16]Diebold F X, Hahn J, Tay A S. Multivariate density forecast evaluation and calibration in financial risk management: High-frequency returns on foreign exchange[J]. The Review of Economics and Statistics, 1999, 81(4): 661-673.

共引文献466

1杨铭.基于Copula模型的金融市场风险测度研究[J].投资与创业,2023,34(1):10-12. 被引量：1
2陈文生,侯成琪.黄金具有对冲和避险属性吗——基于异方差识别法和copula模型的实证分析[J].金融学季刊,2020(4):60-90.
3张瑞,类淑河.基于小波相干的波流相关性分析[J].海洋湖沼通报,2022(6):1-5.
4龙春晓.金融风险控制中流动性风险管理与应对措施[J].现代经济信息,2024(5):148-150.
5杨兴民.基于Elliptical Copula函数的相关性模型研究[J].应用数学与计算数学学报,2007,21(2):111-117.
6孙明明,程希骏.一种选择最优copula的新方法[J].中国科学技术大学学报,2010,40(9):887-891. 被引量：2
7程九思,宋佳宁.证券相关关系度量方法的实证研究[J].吉林金融研究,2011(11):5-11.
8冯绍辉.基于Copula理论的A股与H股尾部相关性研究[J].财会通讯（中）,2011(4):6-7.
9胡啸兵,何旭静,张成虎.中国股票市场流动性与收益率相关分析——基于Copula-GARCH模型的实证研究[J].大连理工大学学报（社会科学版）,2012,33(2):49-53. 被引量：4
10董彬彬.中国沪深股市相关性研究[J].市场周刊,2010,23(1):61-63. 被引量：2

同被引文献15

1李平,马婷婷.基于Copula的我国商业银行整体风险度量[J].硅谷,2008,1(12):148-149. 被引量：5
2童勇.资本结构的动态调整和影响因素[J].财经研究,2004,30(10):96-104. 被引量：80
3BANERJEE H, HESHMATI A, WIHLBORG C. The dynamics of capital structure, stockolm school of economics[M]. Working Paper Series in Economics and Finance, 2000 : 333.
4MARK J FLANNERY, KASTURI P. Rangan partial adjustment toward target capital structures [J]. Journal of Financial Eeonomies, 2006,79:469-- 506.
5HESHMATI. The dynamincs of capital structure: Evidence from swedish micro and small firms[J]. Research in Banking and Finance, 2002,2:199 -- 241.
6HANS LOOFS. Dynamic optimal capital structure and technological change[M]. Centre for European Economic Research Discussion Paper, 2004 : 3-- 6.
7GAUD P,JANI E, HOESLI M. The capital structure of Swiss companies: An empirical analysis using dynamic panel data[M]. University of Geneva,Working Paper, 2003 : 1-- 28.
8HALIM MOHD NOOR, ROGER CLARKE, NIGEL DRIFFIELD. Multinational enterprises and technologi- cal effort by local firms: A case study of the Malaysian electronics and electrical industry[J]. The Journal of Development Studies, Taylor and Francis Journals, 2002,38(6):129-141.
9DE MIGUEL A, PINDADO J. Determinants of capital structure : New evidence from Spanish panel data[J].Journal of Corperate Finance, 2001,7:77--99.
10詹原瑞,韩铁,马珊珊.基于copula函数族的信用违约互换组合定价模型[J].中国管理科学,2008,16(1):1-6. 被引量：25