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    <title>Grubišić, I.</title>
    <link>http://repub.eur.nl/res/aut/6423/</link>
    <description>List of Publications</description>
    <language>en</language>
    <image>
      <url>http://repub.eur.nl/static-eur/img/logo.png</url>
      <title>RePub, Erasmus University Rotterdam</title>
      <link>http://repub.eur.nl</link>
    </image>
    <item>
      <title>Efficient Rank Reduction of Correlation Matrices (Research Paper)</title>
      <link>http://repub.eur.nl/res/pub/1933/</link>
      <pubDate>2005-04-03T00:00:00Z</pubDate>
      <description>Geometric optimisation algorithms are developed that efficiently find the nearest low-rank
correlation matrix. We show, in numerical tests, that our methods compare favourably to the
existing methods in the literature. The connection with the Lagrange multiplier method is
established, along with an identification of whether a local minimum is a global minimum. An
additional benefit of the geometric approach is that any weighted norm can be applied. The
problem of finding the nearest low-rank correlation matrix occurs as part of the calibration of
multi-factor interest rate market models to correlation.</description>
    </item>
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