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Bayesian analysis of multiple thresholds autoregressive model

Author

Listed:
  • Jiazhu Pan

    (University of Strathclyde)

  • Qiang Xia

    (South China Agricultural University)

  • Jinshan Liu

    (South China Agricultural University)

Abstract

Bayesian analysis of threshold autoregressive (TAR) model with various possible thresholds is considered. A method of Bayesian stochastic search selection is introduced to identify a threshold-dependent sequence with highest probability. All model parameters are computed by a hybrid Markov chain Monte Carlo method, which combines Metropolis–Hastings algorithm and Gibbs sampler. The main innovation of the method introduced here is to estimate the TAR model without assuming the fixed number of threshold values, thus is more flexible and useful. Simulation experiments and a real data example lend further support to the proposed approach.

Suggested Citation

  • Jiazhu Pan & Qiang Xia & Jinshan Liu, 2017. "Bayesian analysis of multiple thresholds autoregressive model," Computational Statistics, Springer, vol. 32(1), pages 219-237, March.
    • Handle: RePEc:spr:compst:v:32:y:2017:i:1:d:10.1007_s00180-016-0673-3
    DOI: 10.1007/s00180-016-0673-3
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    References listed on IDEAS

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    3. Cathy W. S. Chen & Mike K. P. So & Ming-Tien Chen, 2005. "A Bayesian threshold nonlinearity test for financial time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(1), pages 61-75.
    4. John Geweke & Nobuhiko Terui, 1993. "Bayesian Threshold Autoregressive Models For Nonlinear Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(5), pages 441-454, September.
    5. Chen, Cathy W. S., 1998. "A Bayesian analysis of generalized threshold autoregressive models," Statistics & Probability Letters, Elsevier, vol. 40(1), pages 15-22, September.
    6. Mohamed A. Ismail & Husni A. Charif, 2003. "Bayesian inference for threshold moving average models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 119-132.
    7. Chris Brooks & Ian Garrett, 2002. "Can we explain the dynamics of the UK FTSE 100 stock and stock index futures markets?," Applied Financial Economics, Taylor & Francis Journals, vol. 12(1), pages 25-31.
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    Cited by:

    1. Xiaobing Zheng & Kun Liang & Qiang Xia & Dabin Zhang, 2022. "Best Subset Selection for Double-Threshold-Variable Autoregressive Moving-Average Models: The Bayesian Approach," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1175-1201, March.
    2. Varun Agiwal & Jitendra Kumar, 2020. "Bayesian estimation for threshold autoregressive model with multiple structural breaks," METRON, Springer;Sapienza Università di Roma, vol. 78(3), pages 361-382, December.
    3. Muhammad Jaffri Mohd Nasir & Ramzan Nazim Khan & Gopalan Nair & Darfiana Nur, 2024. "Active-set based block coordinate descent algorithm in group LASSO for self-exciting threshold autoregressive model," Statistical Papers, Springer, vol. 65(5), pages 2973-3006, July.

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