IDEAS home Printed from https://ideas.repec.org/p/cte/wsrepe/ws041305.html
   My bibliography  Save this paper

Variance changes detection in multivariate time series

Author

Listed:
  • Galeano, Pedro
  • Peña, Daniel

Abstract

This paper studies the detection of step changes in the variances and in the correlation structure of the components of a vector of time series. Two procedures are considered. The first is based on the likelihood ratio test and the second on cusum statistics. These two procedures are compared in a simulation study and we conclude that the cusum procedure is more powerful. The procedures are illustrated in two examples.R

Suggested Citation

  • Galeano, Pedro & Peña, Daniel, 2004. "Variance changes detection in multivariate time series," DES - Working Papers. Statistics and Econometrics. WS ws041305, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:ws041305
    as

    Download full text from publisher

    File URL: https://e-archivo.uc3m.es/rest/api/core/bitstreams/de73ef67-0083-4945-930f-d498e45b11cd/content
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sangyeol Lee & Siyun Park, 2001. "The Cusum of Squares Test for Scale Changes in Infinite Order Moving Average Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(4), pages 625-644, December.
    2. Ulrich Menzefricke, 1981. "A Bayesian Analysis of a Change in the Precision of a Sequence of Independent Normal Random Variables at an Unknown Time Point," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 30(2), pages 141-146, June.
    3. D. A. Hsu, 1977. "Tests for Variance Shift at an Unknown Time Point," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 26(3), pages 279-284, November.
    4. Lutkepohl, Helmut & Poskitt, D S, 1996. "Specification of Echelon-Form VARMA Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 69-79, January.
    5. Howard Grubb, 1992. "A Multivariate Time Series Analysis of Some Flour Price Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(1), pages 95-107, March.
    6. B. Abraham & W. Wei, 1984. "Inferences about the parameters of a time series model with changing variance," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 31(1), pages 183-194, December.
    7. Booth, N.B. & Smith, A.F.M., 1982. "A Bayesian approach to retrospective identification of change-points," Journal of Econometrics, Elsevier, vol. 19(1), pages 7-22, May.
    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. Pedro Galeano & Dominik Wied, 2017. "Dating multiple change points in the correlation matrix," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 331-352, June.
    2. Dominik Wied, 2017. "A nonparametric test for a constant correlation matrix," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1157-1172, November.
    3. Xu, Ke-Li & Phillips, Peter C.B., 2008. "Adaptive estimation of autoregressive models with time-varying variances," Journal of Econometrics, Elsevier, vol. 142(1), pages 265-280, January.
    4. Herwartz, Helmut & Morales-Arias, Leonardo, 2010. "An empirical analysis of the relationship between US monetary policy and international asset prices," Kiel Working Papers 1581, Kiel Institute for the World Economy (IfW Kiel).
    5. Josua Gösmann & Daniel Ziggel, 2018. "An innovative risk management methodology for trading equity indices based on change points," Journal of Asset Management, Palgrave Macmillan, vol. 19(2), pages 99-109, March.
    6. Dominik Wied & Matthias Arnold & Nicolai Bissantz & Daniel Ziggel, 2012. "A new fluctuation test for constant variances with applications to finance," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(8), pages 1111-1127, November.

    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. Minya Xu & Ping-Shou Zhong & Wei Wang, 2016. "Detecting Variance Change-Points for Blocked Time Series and Dependent Panel Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 213-226, April.
    2. Xu, Ke-Li & Phillips, Peter C.B., 2008. "Adaptive estimation of autoregressive models with time-varying variances," Journal of Econometrics, Elsevier, vol. 142(1), pages 265-280, January.
    3. George Athanasopoulos & Farshid Vahid, 2008. "A complete VARMA modelling methodology based on scalar components," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(3), pages 533-554, May.
    4. Baisuo Jin & Mong-Na Lo Huang & Baiqi Miao, 2011. "Testing for variance changes in autoregressive models with unknown order," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(5), pages 927-936, January.
    5. Wenzhi Zhao & Zheng Tian & Zhiming Xia, 2010. "Ratio test for variance change point in linear process with long memory," Statistical Papers, Springer, vol. 51(2), pages 397-407, June.
    6. de Pooter, M.D. & van Dijk, D.J.C., 2004. "Testing for changes in volatility in heteroskedastic time series - a further examination," Econometric Institute Research Papers EI 2004-38, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Ewing, Bradley T. & Malik, Farooq, 2016. "Volatility spillovers between oil prices and the stock market under structural breaks," Global Finance Journal, Elsevier, vol. 29(C), pages 12-23.
    8. Hao Jin & Si Zhang & Jinsuo Zhang, 2017. "Spurious regression due to neglected of non-stationary volatility," Computational Statistics, Springer, vol. 32(3), pages 1065-1081, September.
    9. René Lalonde & Jennifer Page & Pierre St-Amant, 1998. "Une nouvelle méthode d'estimation de l'écart de production et son application aux États-Unis, au Canada et à l'Allemagne," Staff Working Papers 98-21, Bank of Canada.
    10. Hui Hong & Zhicun Bian & Chien-Chiang Lee, 2021. "COVID-19 and instability of stock market performance: evidence from the U.S," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
    11. DUFOUR, Jean-Marie & JOUINI, Tarek, 2005. "Asymptotic Distribution of a Simple Linear Estimator for VARMA Models in Echelon Form," Cahiers de recherche 10-2005, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    12. Alessandro De Gregorio & Stefano Iacus, 2007. "Change point estimation for the telegraph process observed at discrete times," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1053, Universitá degli Studi di Milano.
    13. Stefan Albert & Michael Messer & Julia Schiemann & Jochen Roeper & Gaby Schneider, 2017. "Multi-Scale Detection of Variance Changes in Renewal Processes in the Presence of Rate Change Points," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 1028-1052, November.
    14. Rosalia Condorelli, 2013. "A Bayesian analysis of suicide data," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 1143-1161, February.
    15. Kucharczyk, Daniel & Wyłomańska, Agnieszka & Sikora, Grzegorz, 2018. "Variance change point detection for fractional Brownian motion based on the likelihood ratio test," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 439-450.
    16. Dias, Gustavo Fruet & Kapetanios, George, 2018. "Estimation and forecasting in vector autoregressive moving average models for rich datasets," Journal of Econometrics, Elsevier, vol. 202(1), pages 75-91.
    17. Alfredo Garcia-Hiernaux & Jose Casals & Miguel Jerez, 2024. "Identification of canonical models for vectors of time series: a subspace approach," Statistical Papers, Springer, vol. 65(3), pages 1493-1530, May.
    18. Chan, Joshua C.C. & Eisenstat, Eric & Koop, Gary, 2016. "Large Bayesian VARMAs," Journal of Econometrics, Elsevier, vol. 192(2), pages 374-390.
    19. Dupasquier, Chantal & Guay, Alain & St-Amant, Pierre, 1999. "A Survey of Alternative Methodologies for Estimating Potential Output and the Output Gap," Journal of Macroeconomics, Elsevier, vol. 21(3), pages 577-595, July.
    20. Chen, Cathy W.S. & Chan, Jennifer S.K. & So, Mike K.P. & Lee, Kevin K.M., 2011. "Classification in segmented regression problems," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2276-2287, July.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cte:wsrepe:ws041305. 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: Ana Poveda (email available below). General contact details of provider: http://portal.uc3m.es/portal/page/portal/dpto_estadistica .

    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.