IDEAS home Printed from https://ideas.repec.org/a/spr/jecfin/v46y2022i3d10.1007_s12197-022-09579-7.html
   My bibliography  Save this article

Evaluating measures of dependence for linearly generated nonlinear time series along with spurious correlation

Author

Listed:
  • Christos Agiakloglou

    (University of Piraeus
    University of Illinois at Urbana-Champaign)

  • Anil Bera

    (University of Illinois at Urbana-Champaign)

  • Emmanouil Deligiannakis

    (University of Piraeus)

Abstract

The issue of determining dependence between two series is typically one of the most important aspects in any quantitative analysis. This study, using a Monte Carlo analysis, investigates the performance of several dependence measures for linearly generated nonlinear time series based on the family of AR(1) – ARCH(1) in variable models presented by Bera et al. (1992 and 1996) and it finds that copulas capture the concept of dependence better than the correlation coefficient. In addition, this study examines the performance of the test for zero association and it discovers that the spurious behavior can be eliminated asymptotically for this type on nonlinear processes, although the power of the test remains relatively low.

Suggested Citation

  • Christos Agiakloglou & Anil Bera & Emmanouil Deligiannakis, 2022. "Evaluating measures of dependence for linearly generated nonlinear time series along with spurious correlation," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 535-552, July.
    • Handle: RePEc:spr:jecfin:v:46:y:2022:i:3:d:10.1007_s12197-022-09579-7
    DOI: 10.1007/s12197-022-09579-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12197-022-09579-7
    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/s12197-022-09579-7?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. Bera, Anil K & Higgins, Matthew L & Lee, Sangkyu, 1992. "Interaction between Autocorrelation and Conditional Heteroscedasticity: A Random-Coefficient Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 133-142, April.
    2. Christos Agiakloglou & Charalampos Agiropoulos, 2016. "The balance between size and power in testing for linear association for two stationary AR(1) processes," Applied Economics Letters, Taylor & Francis Journals, vol. 23(4), pages 230-234, March.
    3. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.
    4. Clive Granger & Namwon Hyung & Yongil Jeon, 2001. "Spurious regressions with stationary series," Applied Economics, Taylor & Francis Journals, vol. 33(7), pages 899-904.
    5. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    6. Ning, Cathy, 2010. "Dependence structure between the equity market and the foreign exchange market-A copula approach," Journal of International Money and Finance, Elsevier, vol. 29(5), pages 743-759, September.
    7. Banerjee, Anindya & Dolado, Juan J. & Galbraith, John W. & Hendry, David, 1993. "Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data," OUP Catalogue, Oxford University Press, number 9780198288107.
    8. Granger Clive W.J., 2008. "Non-Linear Models: Where Do We Go Next - Time Varying Parameter Models?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-11, September.
    9. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Chen, Wei-Peng & Choudhry, Taufiq & Wu, Chih-Chiang, 2013. "The extreme value in crude oil and US dollar markets," Journal of International Money and Finance, Elsevier, vol. 36(C), pages 191-210.
    2. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    3. Travaglini, Guido, 2007. "The U.S. Dynamic Taylor Rule With Multiple Breaks, 1984-2001," MPRA Paper 3419, University Library of Munich, Germany, revised 15 Jun 2007.
    4. Bai, Xiwen, 2021. "Tanker freight rates and economic policy uncertainty: A wavelet-based copula approach," Energy, Elsevier, vol. 235(C).
    5. Mokni, Khaled & Mansouri, Faysal, 2017. "Conditional dependence between international stock markets: A long memory GARCH-copula model approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 116-131.
    6. Tong, Bin & Diao, Xundi & Wu, Chongfeng, 2015. "Modeling asymmetric and dynamic dependence of overnight and daytime returns: An empirical evidence from China Banking Sector," Economic Modelling, Elsevier, vol. 51(C), pages 366-382.
    7. Md. Abu HASAN, 2017. "Efficiency and Volatility of the Stock Market in Bangladesh: A Macroeconometric Analysis," Turkish Economic Review, KSP Journals, vol. 4(2), pages 239-249, June.
    8. Singh, Tarlok, 2008. "Testing the Saving-Investment correlations in India: An evidence from single-equation and system estimators," Economic Modelling, Elsevier, vol. 25(5), pages 1064-1079, September.
    9. Committee, Nobel Prize, 2003. "Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity," Nobel Prize in Economics documents 2003-1, Nobel Prize Committee.
    10. Charles G. Renfro, 2009. "The Practice of Econometric Theory," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75571-5.
    11. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911, September.
    12. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, June.
    13. Garcia-Jorcano, Laura & Benito, Sonia, 2020. "Studying the properties of the Bitcoin as a diversifying and hedging asset through a copula analysis: Constant and time-varying," Research in International Business and Finance, Elsevier, vol. 54(C).
    14. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    15. Michael C. Dillbeck & Kenneth L. Cavanaugh, 2016. "Societal Violence and Collective Consciousness," SAGE Open, , vol. 6(2), pages 21582440166, April.
    16. D. Ventosa-Santaulària, 2009. "Spurious Regression," Journal of Probability and Statistics, Hindawi, vol. 2009, pages 1-27, August.
    17. Tong, Bin & Wu, Chongfeng & Zhou, Chunyang, 2013. "Modeling the co-movements between crude oil and refined petroleum markets," Energy Economics, Elsevier, vol. 40(C), pages 882-897.
    18. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    19. N. Vijayamohanan Pillai, 2010. "Electricity Demand Analysis and Forecasting- The Tradition is Questioned," Working Papers id:2966, eSocialSciences.
    20. Çekin, Semih Emre & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "Measuring co-dependencies of economic policy uncertainty in Latin American countries using vine copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 207-217.

    More about this item

    Keywords

    Correlation coefficient; Copulas; Non-linear time series; Spurious correlation; Monte Carlo Analysis;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:spr:jecfin:v:46:y:2022:i:3:d:10.1007_s12197-022-09579-7. 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.