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On the robustness of least-squares Monte Carlo (LSM) for pricing American derivatives

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  • Manuel Moreno
  • Javier R. Navas

Abstract

This paper analyses the robustness of Least-Squares Monte Carlo, a technique recently proposed by Longstaff and Schwartz (2001) for pricing American options. This method is based on least-squares regressions in which the explanatory variables are certain polynomial functions. We analyze the impact of different basis functions on option prices. Numerical results for American put options provide evidence that a) this approach is very robust to the choice of different alternative polynomials and b) few basis functions are required. However, these conclusions are not reached when analyzing more complex derivatives.

Suggested Citation

  • Manuel Moreno & Javier R. Navas, 2001. "On the robustness of least-squares Monte Carlo (LSM) for pricing American derivatives," Economics Working Papers 543, Department of Economics and Business, Universitat Pompeu Fabra.
  • Handle: RePEc:upf:upfgen:543
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    1. Huang, Jing-zhi & Subrahmanyam, Marti G & Yu, G George, 1996. "Pricing and Hedging American Options: A Recursive Integration Method," Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 277-300.
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    Cited by:

    1. Berridge, S.J. & Schumacher, J.M., 2002. "An Irregular Grid Approach for Pricing High Dimensional American Options," Discussion Paper 2002-99, Tilburg University, Center for Economic Research.
    2. Caporale, Guglielmo Maria & Cerrato, Mario, 2008. "Chebyshev polynomial approximation to approximate partial differential equations," SIRE Discussion Papers 2008-15, Scottish Institute for Research in Economics (SIRE).
    3. D. Andricopoulos, Ari & Widdicks, Martin & Newton, David P. & Duck, Peter W., 2007. "Extending quadrature methods to value multi-asset and complex path dependent options," Journal of Financial Economics, Elsevier, vol. 83(2), pages 471-499, February.
    4. Minqiang Li, 2010. "A quasi-analytical interpolation method for pricing American options under general multi-dimensional diffusion processes," Review of Derivatives Research, Springer, vol. 13(2), pages 177-217, July.
    5. Miranda Sarmento, J. & Renneboog, L.D.R., 2014. "Public-Private Partnerships : Risk Allocation and Value for Money," Discussion Paper 2014-017, Tilburg University, Tilburg Law and Economic Center.
    6. Farid AitSahlia & Manisha Goswami & Suchandan Guha, 2010. "American option pricing under stochastic volatility: an efficient numerical approach," Computational Management Science, Springer, vol. 7(2), pages 171-187, April.
    7. Marta Biancardi & Giovanni Villani, 2017. "Robust Monte Carlo Method for R&D Real Options Valuation," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 481-498, March.
    8. Andrea Gamba & Nicola Fusari, 2009. "Valuing Modularity as a Real Option," Management Science, INFORMS, vol. 55(11), pages 1877-1896, November.
    9. Nelson Areal & Artur Rodrigues & Manuel Armada, 2008. "On improving the least squares Monte Carlo option valuation method," Review of Derivatives Research, Springer, vol. 11(1), pages 119-151, March.
    10. repec:spr:lnecms:978-3-540-48264-2 is not listed on IDEAS
    11. Cartea, Álvaro & Williams, Thomas, 2008. "UK gas markets: The market price of risk and applications to multiple interruptible supply contracts," Energy Economics, Elsevier, vol. 30(3), pages 829-846, May.
    12. Andrea Gamba, 2002. "Real options Valuation: A Monte Carol Approach," Working Papers wpn02-02, Warwick Business School, Finance Group.
    13. Alonso-Conde, Ana Belen & Brown, Christine & Rojo-Suarez, Javier, 2007. "Public private partnerships: Incentives, risk transfer and real options," Review of Financial Economics, Elsevier, vol. 16(4), pages 335-349.
    14. repec:spr:fininn:v:2:y:2016:i:1:d:10.1186_s40854-015-0019-0 is not listed on IDEAS
    15. Jonathan A. Batten & Karren Lee-Hwei Khaw & Martin R. Young, 2014. "Convertible Bond Pricing Models," Journal of Economic Surveys, Wiley Blackwell, vol. 28(5), pages 775-803, December.
    16. Piotr Komański & Oskar Sokoliński, 2015. "Least-Squares Monte Carlo Simulation for Time Value of Options and Guarantees Calculation," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 41.
    17. Zhu, Lei & Zhang, ZhongXiang & Fan, Ying, 2015. "Overseas oil investment projects under uncertainty: How to make informed decisions?," Journal of Policy Modeling, Elsevier, vol. 37(5), pages 742-762.
    18. Edoli, Enrico & Fiorenzani, Stefano & Ravelli, Samuele & Vargiolu, Tiziano, 2013. "Modeling and valuing make-up clauses in gas swing contracts," Energy Economics, Elsevier, vol. 35(C), pages 58-73.
    19. Carmona, Julio & León, Angel & Vaello-Sebastià, Antoni, 2012. "Does stock return predictability affect ESO fair value?," European Journal of Operational Research, Elsevier, vol. 223(1), pages 188-202.
    20. Cassimon, D. & Engelen, P.J. & Thomassen, L. & Van Wouwe, M., 2007. "Closed-form valuation of American call options on stocks paying multiple dividends," Finance Research Letters, Elsevier, vol. 4(1), pages 33-48, March.
    21. repec:eee:ejores:v:263:y:2017:i:2:p:698-706 is not listed on IDEAS
    22. Lars Stentoft, 2013. "American option pricing using simulation with an application to the GARCH model," Chapters,in: Handbook of Research Methods and Applications in Empirical Finance, chapter 5, pages 114-147 Edward Elgar Publishing.
    23. S. Alonso & V. Azofra & G. De La Fuente, 2014. "What do you do when the binomial cannot value real options? The LSM model," Cogent Economics & Finance, Taylor & Francis Journals, vol. 2(1), pages 1-17, December.
    24. Lars Stentoft, 2004. "Convergence of the Least Squares Monte Carlo Approach to American Option Valuation," Management Science, INFORMS, vol. 50(9), pages 1193-1203, September.
    25. Alexander Boogert & Cyriel de Jong, 2007. "Gas Storage Valuation Using a Monte Carlo Method," Birkbeck Working Papers in Economics and Finance 0704, Birkbeck, Department of Economics, Mathematics & Statistics.

    More about this item

    Keywords

    Least-Squares Monte Carlo; option pricing; American options;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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