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Detection of Multiple Changes of Variance Using Posterior Odds

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  • Inclan, Carla
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    Abstract

    This article uses a Bayesian procedure based on obtaining posterior odds to assess the evidence about the existence of multiple changes of variance in a time series. The approach is developed for sequences of independent observations. An extension to consider autoregressive models is also discussed. The information on the data about the location of the change points and the magnitude of the variances at the different pieces of the series is summarized through posterior distributions. The procedure is illustrated with a well-known financial series.

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    Bibliographic Info

    Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

    Volume (Year): 11 (1993)
    Issue (Month): 3 (July)
    Pages: 289-300

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    Handle: RePEc:bes:jnlbes:v:11:y:1993:i:3:p:289-300

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    Cited by:
    1. Lubos Pástor & Robert F. Stambaugh, . "The Equity Premium and Structural Breaks," Rodney L. White Center for Financial Research Working Papers 21-98, Wharton School Rodney L. White Center for Financial Research.
    2. Terence Chong, 2001. "Estimating the locations and number of change points by the sample-splitting method," Statistical Papers, Springer, vol. 42(1), pages 53-79, January.
    3. Cook, Steven, 2006. "Testing for cointegration in the presence of mis-specified structural change," Statistics & Probability Letters, Elsevier, vol. 76(13), pages 1380-1384, July.
    4. Jean-Yves Pitarakis, 2004. "Least squares estimation and tests of breaks in mean and variance under misspecification," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 32-54, 06.
    5. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
    6. Yuzhi Cai & Neville Davies, 2003. "Monitoring the parameter changes in general ARIMA time series models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(9), pages 983-1001.
    7. Kim, Tae-Hwan & Leybourne, Stephen & Newbold, Paul, 2002. "Unit root tests with a break in innovation variance," Journal of Econometrics, Elsevier, vol. 109(2), pages 365-387, August.

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