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Ergodicity and existence of moments for local mixtures of linear autoregressions

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  • Carvalho, Alexandre
  • Skoulakis, Georgios

Abstract

We consider a class of nonlinear time series expressed as a local mixture of a finite number of linear autoregressions. The mixing weights are continuous functions of lagged observations while the densities of the innovation terms in each autoregression can be very general and are only assumed to possess finite moments of some order. We focus on the probabilistic properties of the model and provide mild sufficient conditions for geometric ergodicity and existence of moments.

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  • Carvalho, Alexandre & Skoulakis, Georgios, 2005. "Ergodicity and existence of moments for local mixtures of linear autoregressions," Statistics & Probability Letters, Elsevier, vol. 71(4), pages 313-322, March.
    • Handle: RePEc:eee:stapro:v:71:y:2005:i:4:p:313-322
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    References listed on IDEAS

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    1. LeBaron, Blake, 1992. "Some Relations between Volatility and Serial Correlations in Stock Market Returns," The Journal of Business, University of Chicago Press, vol. 65(2), pages 199-219, April.
    2. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
    3. Lu, Zudi, 1996. "A note on geometric ergodicity of autoregressive conditional heteroscedasticity (ARCH) model," Statistics & Probability Letters, Elsevier, vol. 30(4), pages 305-311, November.
    4. Lu, Zudi & Jiang, Zhenyu, 2001. "L1 geometric ergodicity of a multivariate nonlinear AR model with an ARCH term," Statistics & Probability Letters, Elsevier, vol. 51(2), pages 121-130, January.
    5. Markku Lanne & Pentti Saikkonen, 2003. "Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes," Journal of Financial Econometrics, Oxford University Press, vol. 1(1), pages 96-125.
    6. An, Hongzhi & Chen, Min & Huang, Fuchun, 1997. "The geometric ergodicity and existence of moments for a class of non-linear time series model," Statistics & Probability Letters, Elsevier, vol. 31(3), pages 213-224, January.
    7. Lee, Oesook & Shin, Dong Wan, 2000. "On geometric ergodicity of the MTAR process," Statistics & Probability Letters, Elsevier, vol. 48(3), pages 229-237, July.
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    Cited by:

    1. Zacharias Psaradakis & Martin Sola & Nicola Spagnolo & Patricio Yunis, 2024. "Predictive Accuracy of Impulse Responses Estimated Using Local Projections and Vector Autoregressions," Department of Economics Working Papers 2024_02, Universidad Torcuato Di Tella.

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