Divergent estimation error in portfolio optimization and in linear regression

I. Kondor, I. Varga-Haszonits

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The problem of estimation error in portfolio optimization is discussed, in the limit where the portfolio size N and the sample size T go to infinity such that their ratio is fixed. The estimation error strongly depends on the ratio N/T and diverges for a critical value of this parameter. This divergence is the manifestation of an algorithmic phase transition, it is accompanied by a number of critical phenomena, and displays universality. As the structure of a large number of multidimensional regression and modelling problems is very similar to portfolio optimization, the scope of the above observations extends far beyond finance, and covers a large number of problems in operations research, machine learning, bioinformatics, medical science, economics, and technology.

Original languageEnglish
Pages (from-to)601-605
Number of pages5
JournalEuropean Physical Journal B
Volume64
Issue number3-4
DOIs
Publication statusPublished - Aug 1 2008

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ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

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