Random, but not so much a parameterization for the returns and correlation matrix of financial time series

André C.R. Martins

Physica A: Statistical Mechanics and its Applications, 2007, vol. 383, issue 2, 527-532

Abstract: A parameterization that is a modified version of a previous work is proposed for the returns and correlation matrix of financial time series and its properties are studied. This parameterization allows easy introduction of non-stationarity and it shows several of the characteristics of the true, observed realizations, such as fat tails, volatility clustering, and a spectrum of eigenvalues of the correlation matrix that can be understood as an extension of Random Matrix Theory results. The predicted behavior of this parameterization for the eigenvalues is compared with the eigenvalues of Brazilian assets and it is shown that those predictions fit the data better than Random Matrix Theory.

Keywords: Correlation matrix; Random Matrix Theory; Time series; Non-stationarity (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:383:y:2007:i:2:p:527-532

DOI: 10.1016/j.physa.2007.02.108

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