• DocumentCode
    2736282
  • Title

    A Hybrid Importance Sampling Algorithm for Value-at-Risk

  • Author

    Dai, Tian-Shyr ; Lin, Shih-Kuei ; Liu, Li-Min

  • Author_Institution
    Nat. Chiao-Tung Univ., Hsinchu
  • fYear
    2007
  • fDate
    5-7 Sept. 2007
  • Firstpage
    208
  • Lastpage
    208
  • Abstract
    Value-at-risk (VaR) provides a number that measures the risk of a financial portfolio under significant loss. Glasser- man et al. suggest that the performance of Mote Calo simulation can be improved by importance sampling. However, their technique might perform poorly for some complex portfolios like shorting straddle options. In this paper, we investigate the hybrid importance sampling algorithm which can efficiently estimate the VaR for complex portfolios.
  • Keywords
    investment; risk analysis; sampling methods; financial portfolio; hybrid importance sampling algorithm; value-at-risk; Finance; Financial management; Information management; Loss measurement; Mathematics; Monte Carlo methods; Portfolios; Reactive power; Risk management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing, Information and Control, 2007. ICICIC '07. Second International Conference on
  • Conference_Location
    Kumamoto
  • Print_ISBN
    0-7695-2882-1
  • Type

    conf

  • DOI
    10.1109/ICICIC.2007.32
  • Filename
    4427853
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2736282