期刊文献+

人民币汇率预期的随机波动模型研究 被引量:10

Study on Stochastic Volatility Model of CNY Exchange Rate Expectation
下载PDF
导出
摘要 以人民币NDF汇率(Non-deliverable Forward rate,无本金交割远期汇率)作为人民币汇率市场预期的替代变量,通过对该变量的时间序列分析,建立汇率预期随机波动模型以刻画人民币汇率预期的波动特征。研究表明,NDF汇率的波动与市场对人民币汇率的预期变化相吻合,管理当局应对此类预期给予重视;人民币汇率预期波动剧烈,具有厚尾、波动群集性、持续性的特征,且具有波动的杠杆效应。这些性质导致市场中一旦出现人民币升值或贬值的预期,其趋势将维持相当长的时间。因此,管理当局应谨慎看待当前人民币汇率的市场预期及由此形成的升值压力,既肯定其中理性及客观的因素,又需对其非线性、过度波动的特征及其危害有充分的认识。采取积极、稳步渐进的方式推进人民币汇率形成机制改革,应该是符合各方利益、且能够避免诸多不利影响的明智之举。 We used NDF (Non-deliverable Forward rate) rate as the proxy parameter of market expectation of CNY exchange rate to analyze expectation mechanism of CNY via time series analytic approaches. Stochastic volatility model was set up to depict CNY volatility characteristics. Our analysis disclosed the volatility of NDF rate resembles market expectation of CNY. We also found the CNY rate expectation was very volatile. The characteristics of NDF volatility include fat tail, volatility clusting, asymmetry and persistence in volatility. All these characteristics result in long lasting expectation for CNY rate and mass deviation from CNY equilibrium rate. The monetary authorities must attach importance to CNY market expectation and appreciation pressure; regard both the objectivity of market expectation and non-linear, over-reacted characteristic. Our analysis comes to the conclusion that the reform of CNY exchange rate mechanism must perform in an active and gradual way, which will greatly reduce systematic risks.
出处 《暨南学报(哲学社会科学版)》 CSSCI 北大核心 2007年第3期21-28,共8页 Jinan Journal(Philosophy and Social Sciences)
基金 教育部高等学校博士学科点专项科研基金资助项目(编号:20050561011)
关键词 人民币汇率 预期 随机波动模型 CNY exchange rate expectation stochastic volatility model
  • 相关文献

参考文献10

  • 1Ma G.N,Ho C.,McCauley R.N.The markets for non-deliverable forwards in Asian currencies[M].BIS Quarterly Review,June 2004.
  • 2任兆璋,宁忠忠.人民币汇率预期的ARCH效应分析[J].华南理工大学学报(自然科学版),2004,32(12):83-88. 被引量:21
  • 3Singleton,K.J..Estimation of affine asset pricing models using the empirical characteristic function[J].Journal of Econometrics,2001,(102).
  • 4Meyer,R.and Yu.J.BUGS for a Bayesian analysis of stochastic volatility models[J].Econometrics Journal,2000,3.
  • 5Engle,Robert F,Patton Andrew J.What good is a volatility model?[J].NYU Stern School of Business,University of California,San Diego,working paper,January,2001.
  • 6Kim,S.,Shephard,N.,Chib,S.Stochastic volatility:likelihook inference and comparison with ARCH models[J].Review of Economic Studies,1998,(65).
  • 7Spiegelhalter,D.J.Thomas,A.,Best,N.G.,Gilks,W.R.,BUGS 0.5 Bayesian inference using Gibbs sampling.(Version ii)[M].Cambridge,UK.MRC Biostatistics Unit.1996.
  • 8Best,N.,Cowles,M.,and Vines,K..Convergence diagnosis and output analysis,software for Gibbs sampling output version 0.30[J].MRC Biostatistics Unit,1999.Institute of Public Health.
  • 9余素红,张世英.SV和GARCH模型拟合优度比较的似然比检验[J].系统工程学报,2004,19(6):625-629. 被引量:19
  • 10Harvey,A.C.and N.Shephard.The estimation of an asymmetric stochastic volatility modl for asset returns[J].Journal of Business and Economic Statistics,1996,(14).

二级参考文献6

  • 1Gourieroux C, Monfort A. Likelihood ratio statistic[J]. Journal of Econometrics, 1994, 23: 56-78.
  • 2Durbin J, Koopman S J. Monte Carlo maximum likelihood estimation for non-Gaussian state space models[J]. Biometrica, 1997,84: 669-684.
  • 3Ruiz E. Quasi-maximum likelihood estimation of stochastic volatility models[ J]. Journal of Econometrics, 1994, 63: 289-306.
  • 4Engle R F, Bollerslev T. Modeling the persistence of conditional variance [J]. Econometric Review, 1986, 5: 1-50.
  • 5Engle R F. Autoregressive conditional heteroskedasticity with estimates of the variance of the united kingdom inflation [ J]. Econometrica, 1982,50:987 - 1008.
  • 6Engel Lilien D M,Robbins R P. Estimating time varying risk premia in the term structure: The ARCH-M model[J]. Econometrica, 1987,55:391 - 407.

共引文献38

同被引文献68

二级引证文献31

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部