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Adjoint-based Monte Carlo calibration of financial market models

Author

Listed:
  • C. Kaebe

    ()

  • J. Maruhn

    ()

  • E. Sachs

    ()

Abstract

No abstract is available for this item.

Suggested Citation

  • C. Kaebe & J. Maruhn & E. Sachs, 2009. "Adjoint-based Monte Carlo calibration of financial market models," Finance and Stochastics, Springer, vol. 13(3), pages 351-379, September.
  • Handle: RePEc:spr:finsto:v:13:y:2009:i:3:p:351-379 DOI: 10.1007/s00780-009-0097-9
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    File URL: http://hdl.handle.net/10.1007/s00780-009-0097-9
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    References listed on IDEAS

    as
    1. Roger Lord & Remmert Koekkoek & Dick Van Dijk, 2010. "A comparison of biased simulation schemes for stochastic volatility models," Quantitative Finance, Taylor & Francis Journals, vol. 10(2), pages 177-194.
    2. Hull, John C & White, Alan D, 1987. " The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
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    Cited by:

    1. Cristian Homescu, 2011. "Adjoints and Automatic (Algorithmic) Differentiation in Computational Finance," Papers 1107.1831, arXiv.org.
    2. Eichler Andreas & Leobacher Gunther & Zellinger Heidrun, 2011. "Calibration of financial models using quasi-Monte Carlo," Monte Carlo Methods and Applications, De Gruyter, vol. 17(2), pages 99-131, January.

    More about this item

    Keywords

    Adjoint equation; Monte Carlo calibration; Multi-layer method; 65C05; 65K05; 90C30; 90C90; 91B28; C61; C63;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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