Multilevel Monte Carlo methods for applications in finance
Mike Giles, Lukasz Szpruch
TL;DR
This paper reviews the development of multilevel Monte Carlo methods in computational finance, emphasizing variance convergence and future research directions.
Contribution
It provides a comprehensive survey of multilevel Monte Carlo techniques in finance and discusses key features for improving variance convergence.
Findings
Highlights the rapid development of multilevel Monte Carlo in finance
Identifies key features for high variance convergence
Suggests future research directions
Abstract
Since Giles introduced the multilevel Monte Carlo path simulation method [18], there has been rapid development of the technique for a variety of applications in computational finance. This paper surveys the progress so far, highlights the key features in achieving a high rate of multilevel variance convergence, and suggests directions for future research.
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Taxonomy
TopicsMathematical Approximation and Integration · Stochastic processes and financial applications · Statistical Methods and Inference