IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v436y2015icp387-398.html

Estimation of connectivity measures in gappy time series

Author

Listed:
  • Papadopoulos, G.
  • Kugiumtzis, D.

Abstract

A new method is proposed to compute connectivity measures on multivariate time series with gaps. Rather than removing or filling the gaps, the rows of the joint data matrix containing empty entries are removed and the calculations are done on the remainder matrix. The method, called measure adapted gap removal (MAGR), can be applied to any connectivity measure that uses a joint data matrix, such as cross correlation, cross mutual information and transfer entropy. MAGR is favorably compared using these three measures to a number of known gap-filling techniques, as well as the gap closure. The superiority of MAGR is illustrated on time series from synthetic systems and financial time series.

Suggested Citation

  • Papadopoulos, G. & Kugiumtzis, D., 2015. "Estimation of connectivity measures in gappy time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 387-398.
    • Handle: RePEc:eee:phsmap:v:436:y:2015:i:c:p:387-398
    DOI: 10.1016/j.physa.2015.05.032
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437115004471
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2015.05.032?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 look for a different version below or

    for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Warga, Arthur, 1992. "Bond Returns, Liquidity, and Missing Data," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 27(4), pages 605-617, December.
    2. Diks Cees & Manzan Sebastiano, 2002. "Tests for Serial Independence and Linearity Based on Correlation Integrals," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(2), pages 1-22, July.
    3. L. Kullmann & J. Kertesz & K. Kaski, 2002. "Time dependent cross correlations between different stock returns: A directed network of influence," Papers cond-mat/0203256, arXiv.org, revised May 2002.
    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. Papana, Angeliki & Kyrtsou, Catherine & Kugiumtzis, Dimitris & Diks, Cees, 2017. "Financial networks based on Granger causality: A case study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 65-73.
    2. Elsegai, Heba, 2019. "Granger-causality inference in the presence of gaps: An equidistant missing-data problem for non-synchronous recorded time series data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 839-851.

    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. Götze, Tobias & Gürtler, Marc, 2020. "Hard markets, hard times: On the inefficiency of the CAT bond market," Journal of Corporate Finance, Elsevier, vol. 62(C).
    2. Menz, Klaus-Michael, 2010. "Market discipline and the evaluation of Euro financial bonds--An empirical analysis," Research in International Business and Finance, Elsevier, vol. 24(3), pages 315-328, September.
    3. Tsung-Kang Chen & Yijie Tseng & Yu-Ting Hsieh, 2015. "Real Earnings Management Uncertainty and Corporate Credit Risk," European Accounting Review, Taylor & Francis Journals, vol. 24(3), pages 413-440, September.
    4. Favero, Carlo & Pagano, Marco & von Thadden, Ernst-Ludwig, 2010. "How Does Liquidity Affect Government Bond Yields?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(1), pages 107-134, February.
    5. Justo Puerto & Moises Rodr'iguez-Madrena & Andrea Scozzari, 2019. "Location and portfolio selection problems: A unified framework," Papers 1907.07101, arXiv.org.
    6. Arthur Matsuo Yamashita Rios de Sousa & Hideki Takayasu & Misako Takayasu, 2017. "Detection of statistical asymmetries in non-stationary sign time series: Analysis of foreign exchange data," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-18, May.
    7. He, Ling-Yun & Chen, Shu-Peng, 2011. "Nonlinear bivariate dependency of price–volume relationships in agricultural commodity futures markets: A perspective from Multifractal Detrended Cross-Correlation Analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 297-308.
    8. Alexander, Gordon J. & Edwards, Amy K. & Ferri, Michael G., 2000. "The determinants of trading volume of high-yield corporate bonds," Journal of Financial Markets, Elsevier, vol. 3(2), pages 177-204, May.
    9. Dimitri Vayanos & Pierre‐Olivier Weill, 2008. "A Search‐Based Theory of the On‐the‐Run Phenomenon," Journal of Finance, American Finance Association, vol. 63(3), pages 1361-1398, June.
    10. M. Wili'nski & A. Sienkiewicz & T. Gubiec & R. Kutner & Z. R. Struzik, 2013. "Structural and topological phase transitions on the German Stock Exchange," Papers 1301.2530, arXiv.org, revised Jul 2013.
    11. N. C. Suganya & G. A. Vijayalakshmi Pai, 2010. "Pareto‐archived evolutionary wavelet network for financial constrained portfolio optimization," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 17(2), pages 59-90, April.
    12. Dutta, Srimonti & Ghosh, Dipak & Samanta, Shukla, 2014. "Multifractal detrended cross-correlation analysis of gold price and SENSEX," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 195-204.
    13. Výrost, Tomáš & Lyócsa, Štefan & Baumöhl, Eduard, 2015. "Granger causality stock market networks: Temporal proximity and preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 262-276.
    14. Perraudin, William & Taylor, Alex P., 2004. "On the consistency of ratings and bond market yields," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2769-2788, November.
    15. repec:wsi:acsxxx:v:21:y:2018:i:08:n:s0219525918500194 is not listed on IDEAS
    16. Takayuki Mizuno & Shoko Kurihara & Misako Takayasu & Hideki Takayasu, 2003. "Time-scale dependence of correlations among foreign currencies," Papers cond-mat/0303306, arXiv.org.
    17. Bommarito, Michael J. & Duran, Ahmet, 2018. "Spectral analysis of time-dependent market-adjusted return correlation matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 273-282.
    18. Fatica, Serena & Panzica, Roberto, 2024. "Sustainable investing in times of crisis: Evidence from bond holdings and the COVID-19 pandemic," Journal of Banking & Finance, Elsevier, vol. 166(C).
    19. João Henrique Gonçalves Mazzeu & Esther Ruiz & Helena Veiga, 2018. "Uncertainty And Density Forecasts Of Arma Models: Comparison Of Asymptotic, Bayesian, And Bootstrap Procedures," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 388-419, April.
    20. Lu, Erin P. & Lai, Gene C. & Ma, Qingzhong, 2017. "Organizational structure, risk-based capital requirements, and the sales of downgraded bonds," Journal of Banking & Finance, Elsevier, vol. 74(C), pages 51-68.
    21. A. Sienkiewicz & T. Gubiec & R. Kutner & Z. R. Struzik, 2013. "Dynamic structural and topological phase transitions on the Warsaw Stock Exchange: A phenomenological approach," Papers 1301.6506, arXiv.org.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:phsmap:v:436:y:2015:i:c:p:387-398. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.