On toeplitz approximation to empirical correlation matrix of financial asset returns

Document Type

Conference Proceeding

Publication Date

11-12-2012

Abstract

We present a Toeplitz approximation to symmetric empirical correlation matrix of asset returns by auto-regressive order one, AR(1), signal source modeling. AR(1) approximation provides an analytical framework where the corresponding eigenvalues and eigenvectors are defined in closed forms. Furthermore, we show discrete cosine transform (DCT) offers comparable performance to Karhunen-Loeve transform (KLT) for decomposition of empirical correlation matrix of a given portfolio where the first is significantly more efficient to implement. It is concluded that the proposed framework has a potential use for noise filtering and risk management in quantitative finance. © 2012 IEEE.

Identifier

84868517240 (Scopus)

ISBN

[9781467331401]

Publication Title

2012 46th Annual Conference on Information Sciences and Systems Ciss 2012

External Full Text Location

https://doi.org/10.1109/CISS.2012.6310806

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