On the limiting spectral distribution of the covariance matrices of time-lagged processes
Christian Y. Robert and
Mathieu Rosenbaum
Journal of Multivariate Analysis, 2010, vol. 101, issue 10, 2434-2451
Abstract:
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.
Keywords: Eigenvalues; of; covariance; matrices; Lagged; processes; Random; matrix; theory; Time; lag; estimation; Adaptive; estimation (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (6)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:101:y:2010:i:10:p:2434-2451
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