IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v32y2017i1d10.1007_s00180-016-0670-6.html
   My bibliography  Save this article

Scale space multiresolution correlation analysis for time series data

Author

Listed:
  • Leena Pasanen

    (University of Oulu)

  • Lasse Holmström

    (University of Oulu)

Abstract

We propose a new scale space method for the discovery of structure in the correlation between two time series. The method considers the possibility that correlation may not be constant in time and that it might have different features when viewed at different time scales. The time series are first decomposed into additive components corresponding to their features in different time scales. Temporal changes in correlation between pairs of such components are then explored by using weighted correlation within a sliding time window of varying length. Bayesian, sampling-based inference is used to establish the credibility of the correlation structures thus found and the results of analyses are summarized in scale space feature maps. The performance of the method is demonstrated using one artificial and two real data sets. The results underline the usefulness of the scale space approach when the correlation between the time series exhibit time-varying structure in different scales.

Suggested Citation

  • Leena Pasanen & Lasse Holmström, 2017. "Scale space multiresolution correlation analysis for time series data," Computational Statistics, Springer, vol. 32(1), pages 197-218, March.
  • Handle: RePEc:spr:compst:v:32:y:2017:i:1:d:10.1007_s00180-016-0670-6
    DOI: 10.1007/s00180-016-0670-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-016-0670-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00180-016-0670-6?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. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    2. Cochrane, John H, 1989. "The Return of the Liquidity Effect: A Study of the Short-run Relation between Money Growth and Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(1), pages 75-83, January.
    3. Holmström, Lasse & Pasanen, Leena & Furrer, Reinhard & Sain, Stephan R., 2011. "Scale space multiresolution analysis of random signals," Computational Statistics & Data Analysis, Elsevier, vol. 55(10), pages 2840-2855, October.
    4. Erdem, Orhan & Ceyhan, Elvan & Varli, Yusuf, 2014. "A new correlation coefficient for bivariate time-series data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 274-284.
    5. F. Pozzi & T. Matteo & T. Aste, 2012. "Exponential smoothing weighted correlations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 85(6), pages 1-21, June.
    6. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    Full references (including those not matched with items on IDEAS)

    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. Tu, Chengyi, 2014. "Cointegration-based financial networks study in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 402(C), pages 245-254.
    2. Dayong Zhang & Marco R. Barassi & Jijun Tan, 2015. "Residual-Based Tests for Fractional Cointegration: Testing the Term Structure of Interest Rates," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 1118-1140, December.
    3. Biqing Cai & Jiti Gao & Dag Tjøstheim, 2017. "A New Class of Bivariate Threshold Cointegration Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 288-305, April.
    4. Nielsen, Morten Orregaard & Shimotsu, Katsumi, 2007. "Determining the cointegrating rank in nonstationary fractional systems by the exact local Whittle approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 574-596, December.
    5. D. S. Poskitt, 2004. "On The Identification and Estimation of Partially Nonstationary ARMAX Systems," Monash Econometrics and Business Statistics Working Papers 20/04, Monash University, Department of Econometrics and Business Statistics.
    6. Bierens, Herman J., 1997. "Nonparametric cointegration analysis," Journal of Econometrics, Elsevier, vol. 77(2), pages 379-404, April.
    7. Mohamed, Hazik & Masih, Mansur, 2017. "Stock market comovement among the ASEAN-5 : a causality analysis," MPRA Paper 98781, University Library of Munich, Germany.
    8. Muhammad Shahbaz & Syed Jawad Hussain Shahzad & Mantu Kumar Mahalik & Perry Sadorsky, 2018. "How strong is the causal relationship between globalization and energy consumption in developed economies? A country-specific time-series and panel analysis," Applied Economics, Taylor & Francis Journals, vol. 50(13), pages 1479-1494, March.
    9. E.V. Kruglikova & T.K. Blokhina & O.A. Karpenko, 2018. "Current Problems of Banking Supervision and Regulation: A New Evidence," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 40-54.
    10. Erie Febrian & Aldrin Herwany, 2009. "Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets," Working Papers in Economics and Development Studies (WoPEDS) 200911, Department of Economics, Padjadjaran University, revised Sep 2009.
    11. Carmen van der Merwe & Martin de Wit, 2021. "An In-Depth Investigation into the Relationship Between Municipal Solid Waste Generation and Economic Growth in the City of Cape Town," Working Papers 07/2021, Stellenbosch University, Department of Economics, revised 2021.
    12. Hassler, U. & Marmol, F. & Velasco, C., 2006. "Residual log-periodogram inference for long-run relationships," Journal of Econometrics, Elsevier, vol. 130(1), pages 165-207, January.
    13. Arbués, Ignacio & Ledo, Ramiro & Matilla-García, Mariano, 2016. "Automatic identification of general vector error correction models," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-41.
    14. Haldrup, Niels & Nielsen, Morten Orregaard, 2006. "A regime switching long memory model for electricity prices," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 349-376.
    15. Jesus Gonzalo & Tae-Hwy Lee, 2000. "On the robustness of cointegration tests when series are fractionally intergrated," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(7), pages 821-827.
    16. Matheus Koengkan & José Alberto Fuinhas & Renato Santiago, 2020. "Asymmetric impacts of globalisation on CO2 emissions of countries in Latin America and the Caribbean," Environment Systems and Decisions, Springer, vol. 40(1), pages 135-147, March.
    17. Fredj Jawadi & Catherine Bruneau & Nadia Sghaier, 2009. "Nonlinear Cointegration Relationships Between Non‐Life Insurance Premiums and Financial Markets," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(3), pages 753-783, September.
    18. Beare, Brendan K. & Seo, Won-Ki, 2020. "Representation Of I(1) And I(2) Autoregressive Hilbertian Processes," Econometric Theory, Cambridge University Press, vol. 36(5), pages 773-802, October.
    19. Gareth W. Peters & Balakrishnan Kannan & Ben Lasscock & Chris Mellen, 2010. "Model Selection and Adaptive Markov chain Monte Carlo for Bayesian Cointegrated VAR model," Papers 1004.3830, arXiv.org.
    20. Dookie, Michele & Lugay, Beverly & Sergeant, Kelvin A., 2011. "Consumer confidence and economic growth: case studies of Jamaica and Trinidad and Tobago," Sede Subregional de la CEPAL para el Caribe (Estudios e Investigaciones) 4086, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).

    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:spr:compst:v:32:y:2017:i:1:d:10.1007_s00180-016-0670-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.