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Stress indicator construction for internal money market

Author

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  • Isakov , Alexander

    () (Bank of Russia, Moscow, Russia)

Abstract

In this article we propose a modification of time-series segmentation algorithm which allows to identify homogenous periods of money market history by clustering multidimensional probability distributions of relevant variables. We provide step-by-step instructions to systematically choose how many distinct states of the nominal variable is sufficient for precise description of the money market historical conditions and hint at variables which might be suitable for monitoring money market form a central bank’s point of view

Suggested Citation

  • Isakov , Alexander, 2013. "Stress indicator construction for internal money market," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 30(2), pages 77-92.
  • Handle: RePEc:ris:apltrx:0211
    as

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    File URL: http://pe.cemi.rssi.ru/pe_2013_2_77-92.pdf
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    References listed on IDEAS

    as
    1. Berkes, Istv n & Gombay, Edit & Horv th, Lajos & Kokoszka, Piotr, 2004. "SEQUENTIAL CHANGE-POINT DETECTION IN GARCH(p,q) MODELS," Econometric Theory, Cambridge University Press, vol. 20(06), pages 1140-1167, December.
    2. Andrews, Donald W. K. & Lee, Inpyo & Ploberger, Werner, 1996. "Optimal changepoint tests for normal linear regression," Journal of Econometrics, Elsevier, vol. 70(1), pages 9-38, January.
    3. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    money market; time-series; segmentation; probability distribution clustering;

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
    • G19 - Financial Economics - - General Financial Markets - - - Other

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