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

  • Gilles De Truchis


    (AMSE - Aix-Marseille School of Economics - EHESS - École des hautes études en sciences sociales - Centre national de la recherche scientifique (CNRS) - Ecole Centrale Marseille (ECM) - AMU - Aix-Marseille Université)

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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  1. 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.
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  7. Javier Hualde & A Robinson, 2006. "Root-N-Consistent Estimation Of Weakfractional Cointegration," STICERD - Econometrics Paper Series /06/499, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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  11. Balázs Égert & Evžen Kočenda, 2011. "Time-varying synchronization of European stock markets," Empirical Economics, Springer, vol. 40(2), pages 393-407, April.
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  13. 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.
  14. 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.
  15. Frank S. Nielsen, 2009. "Local Whittle estimation of multivariate fractionally integrated processes," CREATES Research Papers 2009-38, School of Economics and Management, University of Aarhus.
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  18. Kpate ADJAOUTE & Jean-Pierre DANTHINE, 2004. "Equity Returns and Integration: Is Europe Changing?," FAME Research Paper Series rp117, International Center for Financial Asset Management and Engineering.
  19. Velasco, Carlos, 1999. "Non-stationary log-periodogram regression," Journal of Econometrics, Elsevier, vol. 91(2), pages 325-371, August.
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  21. Peter M. Robinson & Carlos Velasco, 2000. "Whittle pseudo-maximum likelihood estimation for nonstationary time series," LSE Research Online Documents on Economics 2273, London School of Economics and Political Science, LSE Library.
  22. Cheung, Yin-Wong & Lai, Kon S, 1993. "A Fractional Cointegration Analysis of Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 103-12, January.
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  25. Michael Dueker & Richard Startz, 1998. "Maximum-Likelihood Estimation Of Fractional Cointegration With An Application To U.S. And Canadian Bond Rates," The Review of Economics and Statistics, MIT Press, vol. 80(3), pages 420-426, August.
  26. 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.
  27. Cappiello, Lorenzo & Hördahl, Peter & Kadareja, Arjan & Manganelli, Simone, 2006. "The impact of the euro on financial markets," Working Paper Series 0598, European Central Bank.
  28. Shao, Xiaofeng, 2010. "Nonstationarity-Extended Whittle Estimation," Econometric Theory, Cambridge University Press, vol. 26(04), pages 1060-1087, August.
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