IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v168y2018icp15-17.html
   My bibliography  Save this article

An efficient algorithm to estimate the change in variance

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176518301228
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2018.03.031?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Stenfors, Alexis & Susai, Masayuki, 2021. "Spoofing and pinging in foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eunju Hwang & Dong Wan Shin, 2017. "Stationary bootstrapping for common mean change detection in cross-sectionally dependent panels," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(6), pages 767-787, November.
    2. Shuaimin Kang & Guangying Liu & Howard Qi & Min Wang, 2018. "Bayesian Variance Changepoint Detection in Linear Models with Symmetric Heavy-Tailed Errors," Computational Economics, Springer;Society for Computational Economics, vol. 52(2), pages 459-477, August.
    3. Shi, Yutang, 2015. "Testing change in volatility using panel data," Economics Letters, Elsevier, vol. 134(C), pages 107-110.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:168:y:2018:i:c:p:15-17. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.