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一类GARCH-M模型的遍历性研究（英文） 被引量：1

Ergodicity Study for a GARCH-M Type Model
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摘要 针对Christensen等(2012)提出的一类GARCH-M模型,本文对该模型的遍历性进行了研究.通过对模型的条件均值函数和CARCH方程的参数加以适当的约束条件,模型的几何遍历性可以得到证明.本文的结果可以运用到一些常见GARCH-M模型的条件均值上去. This paper studies the ergodicity of a GARCH-M type model considered by Christensen et al. （2012）. By adopting certain restrictions on mean function and parameters in GARCH equation, geometric ergodicity of the model is proved. The obtained results can be applied to usual conditional mean functions of the GARCH-M models.
作者 张兴发 李元
机构地区 广州大学经济与统计学院
出处 《应用概率统计》 CSCD 北大核心 2015年第3期247-253,共7页 Chinese Journal of Applied Probability and Statistics
基金 supported by National Natural Science Foundation of China(11401123,11271095) Research Fund for the Doctoral Program of Higher Education of China(20124410110002)
关键词 遍历性 GARCH-M模型 李亚普诺夫指数 Ergodicity, GARCH-M model, Lyapounov exponent.
分类号 O211.62 [理学—概率论与数理统计]
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参考文献9

  • 1Christensen, B.J., Dahl, C.M. and Iglesias, E.M., Semiparametric inference in a GARCH-in-mean model, Journal of Econometrics, 167(2)(2012), 458-472.
  • 2Cline, D.B.H., Stability of nonlinear stochastic recursions with application to nonlinear AR-GARCH models, Advances in Applied Probability, 39(2)(2007a), 462-491.
  • 3Cline, D.B.H., Evaluating the Lyapounov exponent and existence of moments for threshold AR-ARCH models, Journal of Time Series Analysis, 28(2)(2007b), 241-260.
  • 4Cline, D.B.H. and Pu, H.H., Geometric ergodicity of nonlinear time series, Statistica Sinica, 9(4) (1999), 1103-1118.
  • 5Engle, R.F., Lilien, D.M. and Robins, R.P., Estimating time varying risk premia in the term structure: the ARCH-M model, Econometrica, 55(2)(1987), 391-407.
  • 6Linton, O.B., Semiparametric and nonparametric ARCH modeling, In: Handbook of Financial Time Series (Editors: Andersen, T.G., Davis, R.A., Kreit3, J.-P. and Mikosch, T.), Springer, 2009, 157-167.
  • 7Meitz, M. and Saikkonen, P., Ergodicity, mixing, and existence of moments of a class of Markov models with applications to GARCH and ACD models, Econometric Theory, 24(5)(2008), 1291-1320.
  • 8Meyn, S.P. and Tweedie, R.L., Markov Chains and Stochastic Stability, Springer-Verlag, London, 1993.
  • 9Severini, T.A. and Wong, W.H., Profile likelihood and conditionally parametric models, The Annals of Statistics, 20(4)(1992), 1768-1802.

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应用概率统计
2015年 第3期

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