Power mapping with dynamical adjustment for improved portfolio optimization

Research output: Contribution to journalArticle

Abstract

For financial risk management it is of vital interest to have good estimates for the correlations between the stocks. It has been found that the correlations obtained from historical data are covered by a considerable amount of noise, which leads to a substantial error in the estimation of the portfolio risk. A method to suppress this noise is power mapping. It raises the absolute value of each matrix element to a power q while preserving the sign. In this paper we use the Markowitz portfolio optimization as a criterion for the optimal value of q and find a K/T dependence, where K is the portfolio size and T the length of the time series. Both in numerical simulations and for real market data we find that power mapping leads to portfolios with considerably reduced risk. It compares well with another noise reduction method based on spectral filtering. A combination of both methods yields the best results.

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Engineering and Technology

Keywords

  • optimization, Numerical simulation, Monte Carlo methods, markets, Financial, Dynamic models, Portfolio, Econophysics, Correlation structures
Original languageEnglish
Pages (from-to)107-119
JournalQuantitative Finance
Volume10
Issue number1
Publication statusPublished - 2010
Publication categoryResearch
Peer-reviewedYes