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An efficient algorithm to estimate the change in variance

Author

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  • Qin, Ruibing
  • Ma, Junjie

Abstract

This article conducts a more exact analysis of the probability of the absolute bias of the popular CUSUM estimator of the variance change, we conclude that the precision of the CUSUM estimator is effected by the location of the variance change and the variances before and behind the change date. And a more efficient estimation is proposed. Simulations demonstrate that the improvement of the proposed method is nontrivial.

Suggested Citation

  • Qin, Ruibing & Ma, Junjie, 2018. "An efficient algorithm to estimate the change in variance," Economics Letters, Elsevier, vol. 168(C), pages 15-17.
    • Handle: RePEc:eee:ecolet:v:168:y:2018:i:c:p:15-17
    DOI: 10.1016/j.econlet.2018.03.031
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    References listed on IDEAS

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    1. Li, Fuxiao & Tian, Zheng & Xiao, Yanting & Chen, Zhanshou, 2015. "Variance change-point detection in panel data models," Economics Letters, Elsevier, vol. 126(C), pages 140-143.
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    Cited by:

    1. Stenfors, Alexis & Susai, Masayuki, 2021. "Spoofing and pinging in foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).
    2. Stenfors, Alexis & Susai, Masayuki, 2019. "Liquidity withdrawal in the FX spot market: A cross-country study using high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 59(C), pages 36-57.
    3. Chen, Zhanshou & Xu, Qiongyao & Li, Huini, 2019. "Inference for multiple change points in heavy-tailed time series via rank likelihood ratio scan statistics," Economics Letters, Elsevier, vol. 179(C), pages 53-56.

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    More about this item

    Keywords

    Change point; Linear processes; CUSUM estimator;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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