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Approximate Whittle analysis of fractional cointegration and the stock market synchronization issue

Author

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  • Gilles De Truchis

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique, EconomiX - EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)

Abstract

I consider a bivariate stationary fractional cointegration system and I propose a quasi-maximum likelihood estimator based on the Whittle analysis of the joint spectral density of the regressor and errors. This allows to estimate jointly all parameters of interest of the model. I lead a Monte Carlo experiment to investigate the finite sample properties of this estimator when integration orders are less than 1/2. However, it is not so easy for practitioners to identify whether or not the observed time series are stationary. This issue is investigated by extending the numerical analysis to mean-reverting non-stationary region of the parameter space, although the proposed estimator is not theoretically designed to handle this case. The results display good finite sample properties in both cases, stationary and non-stationary. Thereby, it reveals that making a wrong decision on the stationarity of raw series does not lead to an erroneous conclusion. An application to the stock market synchronization is proposed to illustrate the empirical relevance of this estimator.

Suggested Citation

  • Gilles De Truchis, 2013. "Approximate Whittle analysis of fractional cointegration and the stock market synchronization issue," Post-Print hal-01498262, HAL.
    • Handle: RePEc:hal:journl:hal-01498262
    DOI: 10.1016/j.econmod.2012.12.011
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. de Truchis, Gilles & Keddad, Benjamin, 2013. "Southeast Asian monetary integration: New evidences from fractional cointegration of real exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 394-412.
    2. Gilles de Truchis & Benjamin Keddad, 2013. "Analyzing Financial Integration in East Asia through Fractional Cointegration in Volatilities," Working Papers halshs-00862256, HAL.
    3. Gilles Truchis & Benjamin Keddad, 2016. "Long-Run Comovements in East Asian Stock Market Volatility," Open Economies Review, Springer, vol. 27(5), pages 969-986, November.
    4. António Afonso & Krzysztof Beck & Karen Jackson, 2022. "Determinants of stock market correlations. Accounting for model uncertainty and reverse causality in a large panel setting," Working Papers REM 2022/0246, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    5. Noureddine Benlagha, 2014. "Dependence structure between nominal and index-linked bond returns: a bivariate copula and DCC-GARCH approach," Applied Economics, Taylor & Francis Journals, vol. 46(31), pages 3849-3860, November.

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    More about this item

    Keywords

    fractional cointegration; Frequency domain; Full-band estimator; Monte Carlo simulation; Parametric; Parametric estimation;
    All these keywords.

    JEL classification:

    • 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
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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