Design of Eigenportfolios for US Equities Using Exponential Correlation Model

Document Type

Conference Proceeding

Publication Date

4-16-2019

Abstract

The eigen decomposition of Toeplitz matrix, with exponential correlations as its elements, to model empirical correlations of US equity returns is investigated. Closed form expressions for eigenvalues and eigenvectors of such Toeplitz matrix are available. Those eigenvectors are used to design the eigenportfolios of the model. The Sharpe ratios and PNL curves of eigenportfolios for stocks in Dow Jones Industrial Average (DJIA) index for the period from July 1999 to Nov. 2018 are calculated to validate the model. The proposed method provides eigenportfolios that closely mimic the eigenportfolios designed based on empirical correlation matrix generated from market data. The modeling of empirical correlation matrix brings new insights to design and evaluate eigenportolios for US equities and other asset classes.

Identifier

85065173522 (Scopus)

ISBN

[9781728111513]

Publication Title

2019 53rd Annual Conference on Information Sciences and Systems Ciss 2019

External Full Text Location

https://doi.org/10.1109/CISS.2019.8692939

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