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On the limiting spectral distribution of the covariance matrices of time-lagged processes

  • Robert, Christian Y.
  • Rosenbaum, Mathieu
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    We consider two continuous-time Gaussian processes, one being partially correlated to a time-lagged version of the other. We first give the limiting spectral distribution for the covariance matrices of the increments of the processes when the span between two observations tends to zero. Then, we derive the limiting distribution of the eigenvalues of the sample covariance matrices. This result is obtained when the number of paths of the processes is asymptotically proportional to the number of observations for each single path. As an application, we use the second moment of this distribution together with auxiliary volatility and correlation estimates to construct an adaptive estimator of the time lag between the two processes. Finally, we provide an asymptotic theory for our estimation procedure.

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    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 101 (2010)
    Issue (Month): 10 (November)
    Pages: 2434-2451

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    Handle: RePEc:eee:jmvana:v:101:y:2010:i:10:p:2434-2451
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    1. Yin, Y. Q. & Krishnaiah, P. R., 1983. "A limit theorem for the eigenvalues of product of two random matrices," Journal of Multivariate Analysis, Elsevier, vol. 13(4), pages 489-507, December.
    2. de Jong, F.C.J.M. & Nijman, T.E., 1995. "High frequency analysis of lead-lag relationships between financial markets," Discussion Paper 1995-34, Tilburg University, Center for Economic Research.
    3. Silverstein, J. W., 1995. "Strong Convergence of the Empirical Distribution of Eigenvalues of Large Dimensional Random Matrices," Journal of Multivariate Analysis, Elsevier, vol. 55(2), pages 331-339, November.
    4. Nijman, T.E. & de Jong, F.C.J.M., 1997. "High frequency analysis of lead-lag relationships between financial markets," Other publications TiSEM f4f406a0-771a-4af2-9364-6, Tilburg University, School of Economics and Management.
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