• DocumentCode
    1909999
  • Title

    Importance sampling for indicator Markov chains

  • Author

    Giesecke, Kay ; Shkolnik, Alexander D.

  • Author_Institution
    Dept. of Manage. Sci. & Eng., Stanford Univ., Stanford, CA, USA
  • fYear
    2010
  • fDate
    5-8 Dec. 2010
  • Firstpage
    2742
  • Lastpage
    2750
  • Abstract
    We consider a continuous-time, inhomogeneous Markov chain M taking values in {0,1}n. Processes of this type arise in finance as models of correlated default timing in a portfolio of firms, in reliability as models of failure timing in a system of interdependent components, and in many other areas. We develop a logarithmically efficient importance sampling scheme for estimating the tail of the distribution of the total transition count of M at a fixed time horizon.
  • Keywords
    Markov processes; estimation theory; importance sampling; investment; correlated default timing model; finance; firm portfolio; importance sampling scheme; indicator Markov chains; tail distribution estimation; Manganese; Markov processes; Monte Carlo methods; Portfolios; Q measurement; Random variables; Timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference (WSC), Proceedings of the 2010 Winter
  • Conference_Location
    Baltimore, MD
  • ISSN
    0891-7736
  • Print_ISBN
    978-1-4244-9866-6
  • Type

    conf

  • DOI
    10.1109/WSC.2010.5678969
  • Filename
    5678969
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1909999