On toeplitz approximation to empirical correlation matrix of financial asset returns

Ali N. Akansu, Mustafa U. Torun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
DOIs
StatePublished - 2012
Event2012 46th Annual Conference on Information Sciences and Systems, CISS 2012 - Princeton, NJ, United States
Duration: Mar 21 2012Mar 23 2012

Publication series

Name2012 46th Annual Conference on Information Sciences and Systems, CISS 2012

Other

Other2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
Country/TerritoryUnited States
CityPrinceton, NJ
Period3/21/123/23/12

All Science Journal Classification (ASJC) codes

  • Information Systems

Keywords

  • AR(1) model
  • Discrete cosine transform
  • Empirical correlation matrix
  • Karhunen-Loeve transform
  • Risk management

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