[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/zbw/espost/200091.html
   My bibliography  Save this article

An Efficient Lattice Algorithm for the LIBOR Market Model

Author

Listed:
  • 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, 2011. "An Efficient Lattice Algorithm for the LIBOR Market Model," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 19(1), pages 25-40.
    • Handle: RePEc:zbw:espost:200091
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/200091/1/Lattice-in-LMM-4.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. Xiao, Tim, 2012. "An Economic Examination of Collateralization in Different Financial Markets," MPRA Paper 47105, University Library of Munich, Germany.
    4. 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.
    5. Tim Xiao, 2017. "A New Model for Pricing Collateralized Financial Derivatives," Post-Print hal-01800559, HAL.
    6. Kian Guan Lim, 2021. "Bermudan option in Singapore Savings Bonds," Review of Derivatives Research, Springer, vol. 24(1), pages 31-54, April.
    7. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pilar Lopez-Llompart & G. Mathias Kondolf, 2016. "Encroachments in floodways of the Mississippi River and Tributaries Project," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 513-542, March.
    2. Michelle Sheran Sylvester, 2007. "The Career and Family Choices of Women: A Dynamic Analysis of Labor Force Participation, Schooling, Marriage and Fertility Decisions," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 10(3), pages 367-399, July.
    3. DAVID M. BLAU & WILBERT van der KLAAUW, 2013. "What Determines Family Structure?," Economic Inquiry, Western Economic Association International, vol. 51(1), pages 579-604, January.
    4. Afanasyev, Dmitriy O. & Fedorova, Elena A. & Popov, Viktor U., 2015. "Fine structure of the price–demand relationship in the electricity market: Multi-scale correlation analysis," Energy Economics, Elsevier, vol. 51(C), pages 215-226.
    5. Peter Viggo Jakobsen, 2009. "Small States, Big Influence: The Overlooked Nordic Influence on the Civilian ESDP," Journal of Common Market Studies, Wiley Blackwell, vol. 47(1), pages 81-102, January.
    6. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2016. "Efficient Gibbs sampling for Markov switching GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 37-57.
    7. Jan Babecký & Fabrizio Coricelli & Roman Horváth, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(2), pages 102-127, June.
    8. Lloyd, S. P., 2017. "Unconventional Monetary Policy and the Interest Rate Channel: Signalling and Portfolio Rebalancing," Cambridge Working Papers in Economics 1735, Faculty of Economics, University of Cambridge.
    9. Ichiro Fukunaga, 2007. "Imperfect Common Knowledge, Staggered Price Setting, and the Effects of Monetary Policy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1711-1739, October.
    10. Albertazzi, Ugo & Gambacorta, Leonardo, 2009. "Bank profitability and the business cycle," Journal of Financial Stability, Elsevier, vol. 5(4), pages 393-409, December.
    11. Beck, Thorsten & Demirgüç-Kunt, Asli & Merrouche, Ouarda, 2013. "Islamic vs. conventional banking: Business model, efficiency and stability," Journal of Banking & Finance, Elsevier, vol. 37(2), pages 433-447.
    12. Jinho Bae & Chang-Jin Kim & Dong Kim, 2012. "The evolution of the monetary policy regimes in the U.S," Empirical Economics, Springer, vol. 43(2), pages 617-649, October.
    13. McMahon, Rob, 2020. "Co-developing digital inclusion policy and programming with indigenous partners: Interventions from Canada," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 9(2), pages 1-26.
    14. George W. Evans & Seppo Honkapohja, 2009. "Robust Learning Stability with Operational Monetary Policy Rules," Central Banking, Analysis, and Economic Policies Book Series, in: Klaus Schmidt-Hebbel & Carl E. Walsh & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Series (ed.),Monetary Policy under Uncertainty and Learning, edition 1, volume 13, chapter 5, pages 145-170, Central Bank of Chile.
    15. Lehtonen, Heikki & Kujala, Sanna, 2007. "Climate change impacts on crop risks and agricultural production in Finland," 101st Seminar, July 5-6, 2007, Berlin Germany 9259, European Association of Agricultural Economists.
    16. Michael Pomerleano, 2011. "Developing Regional Financial Markets – the Case of East Asia," Chapters, in: Ulrich Volz (ed.), Regional Integration, Economic Development and Global Governance, chapter 9, Edward Elgar Publishing.
    17. Gary Charness & Francesco Feri & Miguel A. Meléndez-Jiménez & Matthias Sutter, 2023. "An Experimental Study on the Effects of Communication, Credibility, and Clustering in Network Games," The Review of Economics and Statistics, MIT Press, vol. 105(6), pages 1530-1543, November.
    18. Kitsul, Yuriy & Wright, Jonathan H., 2013. "The economics of options-implied inflation probability density functions," Journal of Financial Economics, Elsevier, vol. 110(3), pages 696-711.
    19. Dieter Balkenborg & Rosemarie Nagel, 2016. "An Experiment on Forward vs. Backward Induction: How Fairness and Level k Reasoning Matter," German Economic Review, Verein für Socialpolitik, vol. 17(3), pages 378-408, August.
    20. J. Park & T. P. Seager & P. S. C. Rao & M. Convertino & I. Linkov, 2013. "Integrating Risk and Resilience Approaches to Catastrophe Management in Engineering Systems," Risk Analysis, John Wiley & Sons, vol. 33(3), pages 356-367, March.

    More about this item

    Keywords

    LIBOR Market Model; lattice model; tree model; shifted forward measure; drift approximation; risk management; calibration; callable exotics; callable bond; callable capped floater swap; callable inverse floater swap; callable range accrual swap;
    All these keywords.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:espost:200091. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.