Option pricing with the control variate technique beyond Monte Carlo simulation
Journal
North American Journal of Economics and Finance
Journal Volume
62
Date Issued
2022-11-01
Author(s)
Abstract
Although mostly used alongside Monte Carlo simulation, the control-variate (CV) technique can be applied to other numerical algorithms in option pricing. This paper studies the conditions under which a numerical method (simulation-based or not) can benefit from the CV technique and what approximators can serve as CVs. We demonstrate the ideas with Carr and Madan's Fourier transform-based algorithm, convolution-based pricing algorithms, and classic binomial trees. Numerical results are provided to show that the CV-enhanced versions are more efficient than the original algorithms.
Subjects
Binomial tree | Control variate | Convolution | Monte Carlo simulation | Numerical algorithm
SDGs
Publisher
ELSEVIER SCIENCE INC
Type
journal article