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<item>
  <id>06097589</id>
  <dt>j</dt>
  <an>06097589</an>
  <augroup>
    <au>Weston, Stephen</au>
    <au>Spooner, James</au>
    <au>Racani\`ere, S\'ebastien</au>
    <au>Mencer, Oskar</au>
  </augroup>
  <ti>Rapid computation of value and risk for derivatives portfolios.</ti>
  <so>Concurrency Comput. Pract. Exp. 24, No. 8, 880-894 (2012).</so>
  <py>2012</py>
  <pu>John Wiley \& Sons, Ltd., Chichester</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>FPGA</ut>
    <ut>J.P. morgan</ut>
    <ut>maxeler</ut>
    <ut>acceleration</ut>
    <ut>credit derivatives</ut>
    <ut>Monte Carlo</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1002/cpe.1778</li>
  </ligroup>
  <abgroup>
    <ab>Summary: We report new results from an on-going project to accelerate derivatives computations. Our earlier work was focused on accelerating the valuation of credit derivatives. In this paper, we extend our work in two ways: by applying the same techniques, first, to accelerate the computation of portfolio level risk for credit derivatives and, second, to different asset classes using a different type of mathematical model, which together present challenges that are quite different to those dealt with in our earlier work. Specifically, we report acceleration over 270 times faster than a single Intel Core for a multi-asset Monte Carlo model. We also explore the implications for risk.</ab>
    <rv></rv>
  </abgroup>
</item>