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Approximate Whittle Analysis of Fractional Cointegration and the Stock Market Synchronization Issue

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  • Gilles De Truchis

    ()
    (AMSE - Aix-Marseille School of Economics - Aix-Marseille Univ. - Centre national de la recherche scientifique (CNRS) - Ecole des Hautes Etudes en Sciences Sociales (EHESS) - Ecole Centrale Marseille (ECM))

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 to estimate jointly all parameters of interest of the model: the long run coefficient and the long memory parameters of the regressor and errors. I lead a Monte Carlo experiment which reveals the good finite sample properties of this estimator, even when the parameter space is extended to the non-stationary regions. An application to the stock market synchronization is proposed to illustrate the empirical relevance of this estimator.

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Paper provided by HAL in its series Working Papers with number halshs-00793220.

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Date of creation: Sep 2012
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Handle: RePEc:hal:wpaper:halshs-00793220

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Related research

Keywords: Fractional cointegration; Frequency domain; Full-band estimator; Monte-Carlo simulation; Parametric estimation;

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References

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  1. Gilmore, Claire G. & McManus, Ginette M., 2002. "International portfolio diversification: US and Central European equity markets," Emerging Markets Review, Elsevier, vol. 3(1), pages 69-83, March.
  2. Morten Ørregaard Nielsen & Per Frederiksen, 2010. "Fully Modified Narrow-Band Least Squares Estimation of Weak Fractional Cointegration," CREATES Research Papers 2010-31, School of Economics and Management, University of Aarhus.
  3. Wälti, Sébastien, 2011. "Stock market synchronization and monetary integration," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 96-110, February.
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  6. Christensen, Bent Jesper & Nielsen, Morten Orregaard, 2006. "Asymptotic normality of narrow-band least squares in the stationary fractional cointegration model and volatility forecasting," Journal of Econometrics, Elsevier, vol. 133(1), pages 343-371, July.
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  9. Nielsen, Morten Orregaard, 2007. "Local Whittle Analysis of Stationary Fractional Cointegration and the ImpliedRealized Volatility Relation," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 427-446, October.
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  14. Velasco, Carlos, 1999. "Non-stationary log-periodogram regression," Journal of Econometrics, Elsevier, vol. 91(2), pages 325-371, August.
  15. Donald W. K. Andrews & Patrik Guggenberger, 2003. "A Bias--Reduced Log--Periodogram Regression Estimator for the Long--Memory Parameter," Econometrica, Econometric Society, vol. 71(2), pages 675-712, March.
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Citations

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Cited by:
  1. Gilles De Truchis & Benjamin Keddad, 2012. "South East Asian Monetary Integration: New Evidences from Fractional Cointegration of Real Exchange Rates," Working Papers halshs-00793503, HAL.
  2. Gilles de Truchis & Benjamin Keddad, 2014. "Analyzing Financial Integration in East Asia through Fractional Cointegration in Volatilities," Working Papers 2014-382, Department of Research, Ipag Business School.

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