A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation

Estimation of high dimensional covariance matrices is an interesting and important research topic. In this thesis, we propose a dynamic structure and develop an estimation procedure for high dimensional covariance matrices. Simulation studies are conducted to demonstrate its performance when the sam...

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Main Author:	Box, John
Published:	University of York 2015
Subjects:	510
Online Access:	http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675092

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spelling	ndltd-bl.uk-oai-ethos.bl.uk-6750922017-10-04T03:18:50ZA dynamic structure for high dimensional covariance matrices and its application in portfolio allocationBox, JohnBox, John2015Estimation of high dimensional covariance matrices is an interesting and important research topic. In this thesis, we propose a dynamic structure and develop an estimation procedure for high dimensional covariance matrices. Simulation studies are conducted to demonstrate its performance when the sample size is finite. By exploring a financial application, an empirical study shows that portfolio allocation based on dynamic high dimensional covariance matrices can significantly outperform the market from 1995 to 2014. Our proposed method also outperforms portfolio allocation based on the sample covariance matrix and the portfolio allocation proposed in Fan, Fan, Lv (2008).510University of Yorkhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675092http://etheses.whiterose.ac.uk/10770/Electronic Thesis or Dissertation
collection	NDLTD
sources	NDLTD
topic	510
spellingShingle	510 Box, John A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation
description	Estimation of high dimensional covariance matrices is an interesting and important research topic. In this thesis, we propose a dynamic structure and develop an estimation procedure for high dimensional covariance matrices. Simulation studies are conducted to demonstrate its performance when the sample size is finite. By exploring a financial application, an empirical study shows that portfolio allocation based on dynamic high dimensional covariance matrices can significantly outperform the market from 1995 to 2014. Our proposed method also outperforms portfolio allocation based on the sample covariance matrix and the portfolio allocation proposed in Fan, Fan, Lv (2008).
author2	Box, John
author_facet	Box, John Box, John
author	Box, John
author_sort	Box, John
title	A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation
title_short	A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation
title_full	A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation
title_fullStr	A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation
title_full_unstemmed	A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation
title_sort	dynamic structure for high dimensional covariance matrices and its application in portfolio allocation
publisher	University of York
publishDate	2015
url	http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.675092
work_keys_str_mv	AT boxjohn adynamicstructureforhighdimensionalcovariancematricesanditsapplicationinportfolioallocation AT boxjohn dynamicstructureforhighdimensionalcovariancematricesanditsapplicationinportfolioallocation
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A dynamic structure for high dimensional covariance matrices and its application in portfolio allocation

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