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Modelling non-linear comovements between time series

Author

Listed:
  • Catherine Kyrtsou

    () (University of Macedonia, Department of Economics)

  • Costas Vorlow

    () (Durham Business School)

Abstract

The main objective of this paper is to employ a new dynamic model that combines the bivariate noisy Mackey–Glass recently proposed by Kyrtsou and Labys [Kyrtsou, C., Labys, W., 2006. Evi- dence for chaotic dependence between US inflation and commodity prices. Journal of Macroeco- nomics 28(1), 256–266; Kyrtsou, C., Labys, W., 2007. Detecting positive feedback in multivariate time series: the case of metal prices and US inflation. Physica A 377(1), 227–229.] and the BEKK Garch processes. An empirical exercise using the US effective Federal fund rates and 3-month T-Bill rates will show that for specific time periods the comovements between series are due to inherent non-linear deterministic dynamics.

Suggested Citation

  • Catherine Kyrtsou & Costas Vorlow, 2008. "Modelling non-linear comovements between time series," Working Papers 2008_01, Durham University Business School.
  • Handle: RePEc:dur:durham:2008_01
    as

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    References listed on IDEAS

    as
    1. Kyrtsou, Catherine & Labys, Walter C., 2007. "Detecting positive feedback in multivariate time series: The case of metal prices and US inflation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 227-229.
    2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
    3. Jean-Luc Demeulemeester & Claude Diebolt, 2007. "How much could economics gain from history: the contribution of cliometrics," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 1(1), pages 7-17, April.
    4. Froyen, Richard T. & Waud, Roger N., 2002. "The determinants of Federal Reserve policy actions: A re-examination," Journal of Macroeconomics, Elsevier, vol. 24(3), pages 413-428, September.
    5. Bali, Turan G. & Wu, Liuren, 2006. "A comprehensive analysis of the short-term interest-rate dynamics," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1269-1290, April.
    6. Haug Alfred A & Siklos Pierre L, 2006. "The Behavior of Short-Term Interest Rates: International Evidence of Non-Linear Adjustment," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(4), pages 1-34, December.
    7. Sarno, Lucio & Thornton, Daniel L., 2003. "The dynamic relationship between the federal funds rate and the Treasury bill rate: An empirical investigation," Journal of Banking & Finance, Elsevier, vol. 27(6), pages 1079-1110, June.
    8. Jess Benhabib & Stephanie Schmitt-Grohé & Martín Uribe, 2002. "Chaotic Interest-Rate Rules," American Economic Review, American Economic Association, vol. 92(2), pages 72-78, May.
    9. Paul Brockman & Mustafa Chowdhury, 1997. "Deterministic versus stochastic volatility: implications for option pricing models," Applied Financial Economics, Taylor & Francis Journals, vol. 7(5), pages 499-505.
    10. Kyrtsou, Catherine & Labys, Walter C., 2006. "Evidence for chaotic dependence between US inflation and commodity prices," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 256-266, March.
    11. Bullard, James & Butler, Alison, 1993. "Nonlinearity and Chaos in Economic Models: Implications for Policy Decisions," Economic Journal, Royal Economic Society, vol. 103(419), pages 849-867, July.
    12. Lucas, Robert E, Jr, 1975. "An Equilibrium Model of the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 83(6), pages 1113-1144, December.
    13. Kyrtsou, Catherine & Malliaris, Anastasios G., 2009. "The impact of information signals on market prices when agents have non-linear trading rules," Economic Modelling, Elsevier, vol. 26(1), pages 167-176, January.
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    Citations

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    Cited by:

    1. Angeliki Papana & Catherine Kyrtsou & Dimitris Kugiumtzis & Cees Diks, 2016. "Detecting Causality in Non-stationary Time Series Using Partial Symbolic Transfer Entropy: Evidence in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 47(3), pages 341-365, March.
    2. Marisa Faggini & Anna Parziale, 2016. "More than 20 years of chaos in economics," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 15(1), pages 53-69, June.
    3. repec:eee:phsmap:v:495:y:2018:i:c:p:225-244 is not listed on IDEAS
    4. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    5. Weihong Huang & Huanhuan Zheng & Wai-Mun Chia, 2013. "Asymmetric returns, gradual bubbles and sudden crashes," The European Journal of Finance, Taylor & Francis Journals, vol. 19(5), pages 420-437, May.
    6. Kyrtsou, Catherine & Mikropoulou, Christina & Papana, Angeliki, 2016. "Does the S&P500 index lead the crude oil dynamics? A complexity-based approach," Energy Economics, Elsevier, vol. 56(C), pages 239-246.
    7. Catherine Kyrtsou & Michel Terraza, 2010. "Seasonal Mackey–Glass–GARCH process and short-term dynamics," Empirical Economics, Springer, vol. 38(2), pages 325-345, April.
    8. Aloui, Chaker & Jammazi, Rania, 2015. "Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 62-86.
    9. Rachida Hennani, 2015. "Can the Lasota(1977)’s model compete with the Mackey-Glass(1977)’s model in nonlinear modelling of financial time series?," Working Papers 15-09, LAMETA, Universtiy of Montpellier, revised Jun 2015.
    10. repec:eee:enepol:v:110:y:2017:i:c:p:686-692 is not listed on IDEAS
    11. Jammazi, Rania & Aloui, Chaker, 2015. "Environment degradation, economic growth and energy consumption nexus: A wavelet-windowed cross correlation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 110-125.

    More about this item

    Keywords

    BEKK Garch and Mackey–Glass processes; Structural changes; Comovements; Interest rates; Non-linear dynamics;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E43 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Interest Rates: Determination, Term Structure, and Effects
    • E59 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Other

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