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Detection of jumps by wavelets in a heteroscedastic autoregressive model

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  • Wong, Heung
  • Ip, Waicheung
  • Li, Yuan
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    Abstract

    Wavelets are applied to detect the jumps in a heteroscedastic autoregressive model. The empirical wavelet coefficients are defined respectively for the conditional mean and the conditional variance of the model. It is shown that the wavelet coefficients exhibit high peaks near the jump points, based on which a procedure is developed to identify and then to locate the jumps. All estimators are shown to be consistent.

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    File URL: http://www.sciencedirect.com/science/article/B6V1D-435KK11-5/2/13e9381e3a0d627cfb8d64a38608123c
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    Bibliographic Info

    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 52 (2001)
    Issue (Month): 4 (May)
    Pages: 365-372

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    Handle: RePEc:eee:stapro:v:52:y:2001:i:4:p:365-372

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    Related research

    Keywords: Heteroscedasticity Autoregressive model Jumps Wavelets;

    References

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    1. Li, C W & Li, W K, 1996. "On a Double-Threshold Autoregressive Heteroscedastic Time Series Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(3), pages 253-74, May-June.
    2. Li, Yuan & Xie, Zhongjie, 1997. "The wavelet detection of hidden periodicities in time series," Statistics & Probability Letters, Elsevier, vol. 35(1), pages 9-23, August.
    3. Aggarwal, Reena & Inclan, Carla & Leal, Ricardo, 1999. "Volatility in Emerging Stock Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(01), pages 33-55, March.
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    Cited by:
    1. Zhou, Yong & Wan, Alan T.K. & Xie, Shangyu & Wang, Xiaojing, 2010. "Wavelet analysis of change-points in a non-parametric regression with heteroscedastic variance," Journal of Econometrics, Elsevier, vol. 159(1), pages 183-201, November.
    2. Yujiao Yang & Qiongxia Song, 2014. "Jump detection in time series nonparametric regression models: a polynomial spline approach," Annals of the Institute of Statistical Mathematics, Springer, vol. 66(2), pages 325-344, April.
    3. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2005. "Nonparametric estimation of structural change points in volatility models for time series," Journal of Econometrics, Elsevier, vol. 126(1), pages 79-114, May.

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