Estimated correlation matrices and portfolio optimization

Szilárd Pafka, Imre Kondor

Research output: Contribution to journalArticle

46 Citations (Scopus)

Abstract

A model-based approach was applied for a systematic investigation of the performance of various noise reduction procedures applied in portfolio selection and risk management. To demonstrate the usefulness of this approach, several toy models were developed for the structure of financial correlations. By considering only the noise arising from the finite length of the model-generated time series, the performance of several correlation matrix estimation procedures were analyzed in a simple portfolio optimization context. The filtering based on random matrix theory was found to be effective.

Original languageEnglish
Pages (from-to)623-634
Number of pages12
JournalPhysica A: Statistical Mechanics and its Applications
Volume343
Issue number1-4
DOIs
Publication statusPublished - Nov 15 2004

Keywords

  • Estimated covariance matrices
  • Estimation noise
  • Noise filtering
  • Portfolio optimization
  • Random matrix theory
  • Risk management

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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