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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, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 30(2), pages 77-92.
    • Handle: RePEc:ris:apltrx:0211
    as

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    References listed on IDEAS

    as
    1. Berkes, István & Gombay, Edit & Horváth, Lajos & Kokoszka, Piotr, 2004. "SEQUENTIAL CHANGE-POINT DETECTION IN GARCH(p,q) MODELS," Econometric Theory, Cambridge University Press, vol. 20(6), pages 1140-1167, December.
    2. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
    3. Robert Tibshirani & Guenther Walther & Trevor Hastie, 2001. "Estimating the number of clusters in a data set via the gap statistic," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(2), pages 411-423.
    4. 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.
    5. Wong, Jian Cheng & Lian, Heng & Cheong, Siew Ann, 2009. "Detecting macroeconomic phases in the Dow Jones Industrial Average time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(21), pages 4635-4645.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    money market; time-series; segmentation; probability distribution clustering;
    All these keywords.

    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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