Uncertainty Quantification of Derivative Instruments

Authors

  • Xianming Sun & Michèle Vanmaele

DOI:

https://doi.org/10.4208/eajam.100316.270117a

Keywords:

Parameter uncertainty, Derivative pricing, Smolyak algorithm, Monte Carlo, Entropy.

Abstract

Model and parameter uncertainties are common whenever some parametric model is selected to value a derivative instrument. Combining the Monte Carlo method with the Smolyak interpolation algorithm, we propose an accurate efficient numerical procedure to quantify the uncertainty embedded in complex derivatives. Except for the value function being sufficiently smooth with respect to the model parameters, there are no requirements on the payoff or candidate models. Numerical tests carried out quantify the uncertainty of Bermudan put options and down-and-out put options under the Heston model, with each model parameter specified in an interval.

Published

2018-03-19

Issue

Section

Articles