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Effective sub-simulation-free upper bounds for the Monte Carlo pricing of callable derivatives and various improvements to existing methodologies

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  • Joshi, Mark
  • Tang, Robert

Abstract

We present a new non-nested approach for computing additive upper bounds for callable derivatives using Monte Carlo simulation. It relies on the regression of Greeks computed using adjoint methods. We also show that it is possible to early terminate paths once points of optimal exercise have been reached. A natural control variate for the multiplicative upper bound is introduced which renders it competitive to the additive one. In addition, a new bi-iterative family of upper bounds is introduced which takes a stopping time, an upper bound, and a martingale as inputs.

Suggested Citation

  • Joshi, Mark & Tang, Robert, 2014. "Effective sub-simulation-free upper bounds for the Monte Carlo pricing of callable derivatives and various improvements to existing methodologies," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 25-45.
    • Handle: RePEc:eee:dyncon:v:40:y:2014:i:c:p:25-45
    DOI: 10.1016/j.jedc.2013.12.001
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ivan Guo & Gregoire Loeper, 2016. "Pricing Bounds for VIX Derivatives via Least Squares Monte Carlo," Papers 1611.00464, arXiv.org.
    2. Nicholas Andrew Yap Swee Guan, 2015. "Regression and Convex Switching System Methods for Stochastic Control Problems with Applications to Multiple-Exercise Options," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 5-2015, January-A.
    3. Ivan Guo & Gregoire Loeper, 2018. "Pricing Bounds for Volatility Derivatives via Duality and Least Squares Monte Carlo," Journal of Optimization Theory and Applications, Springer, vol. 179(2), pages 598-617, November.
    4. Mark S. Joshi, 2016. "Analysing the bias in the primal-dual upper bound method for early exercisable derivatives: bounds, estimation and removal," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 519-533, April.
    5. Nicholas Andrew Yap Swee Guan, 2015. "Regression and Convex Switching System Methods for Stochastic Control Problems with Applications to Multiple-Exercise Options," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 26, July-Dece.

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    More about this item

    Keywords

    G10; G12; G13; LIBOR market model; Bermudan options; Callability; Monte Carlo; Early exercise; Upper bounds;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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