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An Autoregressive Model with Suddenly Changing Parameters and an Application to Stock Market Prices

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  • John S. Tyssedal
  • Dag Tjøstheim

Abstract

We consider autoregressive models where the coefficients are piecewise constant and change according to a Markov chain mechanism. Two methods of estimation are considered: the method of moments and the method of least squares. Moment estimates are shown to be consistent, but simulations show that their convergence could be very slow. Much better results are obtained by a two‐step least squares estimation algorithm. This algorithm is applied on a time series consisting of IBM closing stock prices, and the results are compared with other models that have been fitted to this series. The results are interpreted in the context of some models that are currently used for stock market data, and the major transition points are related to some specific economic events not noted by earlier investigators of the series.

Suggested Citation

  • John S. Tyssedal & Dag Tjøstheim, 1988. "An Autoregressive Model with Suddenly Changing Parameters and an Application to Stock Market Prices," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 37(3), pages 353-369, November.
    • Handle: RePEc:bla:jorssc:v:37:y:1988:i:3:p:353-369
    DOI: 10.2307/2347310
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    Cited by:

    1. Valerie Girardin & Rachid Senoussi, 2020. "Filling the gap between Continuous and Discrete Time Dynamics of Autoregressive Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 590-602, July.
    2. Omokolade Akinsomi & Mehmet Balcilar & Rıza Demirer & Rangan Gupta, 2017. "The effect of gold market speculation on REIT returns in South Africa: a behavioral perspective," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 41(4), pages 774-793, October.
    3. Bucci, Andrea & Ciciretti, Vito, 2022. "Market regime detection via realized covariances," Economic Modelling, Elsevier, vol. 111(C).
    4. Balcilar, Mehmet & Gupta, Rangan & Miller, Stephen M., 2015. "Regime switching model of US crude oil and stock market prices: 1859 to 2013," Energy Economics, Elsevier, vol. 49(C), pages 317-327.
    5. Vassilios Babalos & Mehmet Balcilar & Rangan Gupta, 2014. "Revisiting Herding Behavior in REITs: A Regime-Switching Approach," Working Papers 201448, University of Pretoria, Department of Economics.
    6. Balcılar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2015. "Regional and global spillovers and diversification opportunities in the GCC equity sectors," Emerging Markets Review, Elsevier, vol. 24(C), pages 160-187.
    7. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2013. "Investor herds and regime-switching: Evidence from Gulf Arab stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 295-321.
    8. Balcilar, Mehmet & Hammoudeh, Shawkat & Asaba, Nwin-Anefo Fru, 2015. "A regime-dependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 72-89.
    9. Mehmet Balcilar & Riza Demirer & Shawkat Hammoudeh & Ahmed Khalifa, 2013. "Do Global Shocks Drive Investor Herds in Oil-Rich Frontier Markets?," Working Papers 819, Economic Research Forum, revised Dec 2013.
    10. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2014. "What drives herding in oil-rich, developing stock markets? Relative roles of own volatility and global factors," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 418-440.
    11. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.

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