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High-dimensional autocovariance matrices and optimal linear prediction

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  • Politis, Dimitris

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  • Politis, Dimitris, 2014. "High-dimensional autocovariance matrices and optimal linear prediction," University of California at San Diego, Economics Working Paper Series qt3k58p0xr, Department of Economics, UC San Diego.
    • Handle: RePEc:cdl:ucsdec:qt3k58p0xr
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    References listed on IDEAS

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    1. Efstathios Paparoditis & Dimitris N. Politis, 2012. "Nonlinear spectral density estimation: thresholding the correlogram," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(3), pages 386-397, May.
    2. Politis, Dimitris N., 2011. "Higher-Order Accurate, Positive Semidefinite Estimation Of Large-Sample Covariance And Spectral Density Matrices," Econometric Theory, Cambridge University Press, vol. 27(4), pages 703-744, August.
    3. McMurry, Timothy L & Politis, D N, 2010. "Banded and Tapered Estimates for Autocovariance Matrices and the Linear Process Bootstrap," University of California at San Diego, Economics Working Paper Series qt5h9259mb, Department of Economics, UC San Diego.
    4. Timothy L. McMurry & Dimitris N. Politis, 2010. "Banded and tapered estimates for autocovariance matrices and the linear process bootstrap," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(6), pages 471-482, November.
    5. Ledoit, Olivier & Wolf, Michael, 2003. "Improved estimation of the covariance matrix of stock returns with an application to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 603-621, December.
    6. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
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