ABSTRACT
Chebyshev interpolation is a highly effective, intensively studied method and enjoys excellent numerical properties which provides tremendous application potential in mathematical finance. The interpolation nodes are known beforehand, implementation is straightforward and the method is numerically stable. For efficiency, a sharp error bound is essential, in particular for high-dimensional applications. For tensorized Chebyshev interpolation, we present an error bound that improves existing results significantly.
Acknowledgments
The authors thank the KPMG Center of Excellence in Risk Management of the Technical University of Munich for their support. We acknowledge fruitful discussions with and feedback from Maximilian Gaß, Daniel Kressner, Maximilian Mair and Christian Pötz.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
Kathrin Glau http://orcid.org/0000-0001-6733-1689