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An Efficient Lattice Algorithm For The Libor Market Model

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  • Xiao, Tim

Abstract

The LIBOR Market Model has become one of the most popular models for pricing interest rate products. It is commonly believed that Monte-Carlo simulation is the only viable method available for the LIBOR Market Model. In this article, however, we propose a lattice approach to price interest rate products within the LIBOR Market Model by introducing a shifted forward measure and several novel fast drift approximation methods. This model should achieve the best performance without losing much accuracy. Moreover, the calibration is almost automatic and it is simple and easy to implement. Adding this model to the valuation toolkit is actually quite useful; especially for risk management or in the case there is a need for a quick turnaround.

Suggested Citation

  • Xiao, Tim, 2015. "An Efficient Lattice Algorithm For The Libor Market Model," FrenXiv dxvnw, Center for Open Science.
    • Handle: RePEc:osf:frenxi:dxvnw
    DOI: 10.31219/osf.io/dxvnw
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    1. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
    2. Martzoukos, Spiros H. & Trigeorgis, Lenos, 2002. "Real (investment) options with multiple sources of rare events," European Journal of Operational Research, Elsevier, vol. 136(3), pages 696-706, February.
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    Cited by:

    1. Xiao, Tim, 2012. "An Economic Examination of Collateralization in Different Financial Markets," MPRA Paper 47371, University Library of Munich, Germany.
    2. Xiao, Tim, 2017. "A New Model for Pricing Collateralized OTC Derivatives," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 24(4), pages 8-20.
    3. Zhongkai Liu & Tao Pang, 2016. "An efficient grid lattice algorithm for pricing American-style options," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 5(1), pages 36-55.
    4. Lago, Jesus & De Ridder, Fjo & Vrancx, Peter & De Schutter, Bart, 2018. "Forecasting day-ahead electricity prices in Europe: The importance of considering market integration," Applied Energy, Elsevier, vol. 211(C), pages 890-903.
    5. Xiao, Tim, 2013. "The Impact of Default Dependency and Collateralization on Asset Pricing and Credit Risk Modeling," MPRA Paper 47136, University Library of Munich, Germany.
    6. Tim Xiao, 2017. "A New Model for Pricing Collateralized Financial Derivatives," Post-Print hal-01800559, HAL.
    7. Kian Guan Lim, 2021. "Bermudan option in Singapore Savings Bonds," Review of Derivatives Research, Springer, vol. 24(1), pages 31-54, April.

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    More about this item

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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