Portfolio value at risk based on independent components analysis

Ying Chen, Wolfgang Härdle and Vladimir Spokoiny

No 2005-060, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy tailed distributional properties that are observed in data. A principle component based method (tied closely to the elliptical structure of the distribution) is therefore expected to be unsatisfactory. Here we propose and analyze a technology that is based on Independent Component Analysis (ICA). We study the proposed ICVaR methodology in an extensive simulation study and apply it to a high dimensional portfolio situation. Our analysis yields very accurate VaRs.

Keywords: independent component analysis; Value-at-Risk (search for similar items in EconPapers)
JEL-codes: C14 C15 C32 C53 G20 (search for similar items in EconPapers)
Date: 2005
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