TY - JOUR
T1 - Uncertainty Quantification of Derivative Instruments
AU - Xianming Sun & Michèle Vanmaele
JO - East Asian Journal on Applied Mathematics
VL - 2
SP - 343
EP - 362
PY - 2018
DA - 2018/02
SN - 7
DO - http://doi.org/10.4208/eajam.100316.270117a
UR - https://global-sci.org/intro/article_detail/eajam/10753.html
KW - Parameter uncertainty, Derivative pricing, Smolyak algorithm, Monte Carlo, Entropy.
AB - <p style="text-align: justify;">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.</p>