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International Journal of Computer Mathematics Volume 96, 2019 - Issue 11: International Conference on Computational Finance 2017 (ICCF 2017)
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Improved error bound for multivariate Chebyshev polynomial interpolation

Kathrin GlauSchool of Mathematical Sciences, Queen Mary University of London, London, UK;Department of Mathematics, Technical University of Munich, Munich, GermanyCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-6733-1689
ORCID Icon &
Mirco MahlstedtDepartment of Mathematics, Technical University of Munich, Munich, Germany
Pages 2302-2314 | Received 14 Jan 2018, Accepted 10 Aug 2018, Published online: 15 Apr 2019

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Mike Ludkovski & Yuri Saporito. (2021) KrigHedge: Gaussian Process Surrogates for Delta Hedging. Applied Mathematical Finance 28:4, pages 330-360.
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Ritesh Khan, V.A. Kandappan & Sivaram Ambikasaran. (2024) HODLRdD: A new black-box fast algorithm for N-body problems in d-dimensions with guaranteed error bounds. Journal of Computational Physics 501, pages 112786.
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M. Ludkovski. (2023) Statistical Machine Learning for Quantitative Finance. Annual Review of Statistics and Its Application 10:1, pages 271-295.
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Shuaiqiang Liu, Lech A. Grzelak & Cornelis W. Oosterlee. (2022) The Seven-League Scheme: Deep Learning for Large Time Step Monte Carlo Simulations of Stochastic Differential Equations. Risks 10:3, pages 47.
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Hu Peisen, Li Chuanjun & Yang Yao. (2021) Implementation of sliding interpolation algorithm for equidistant nodes based on BDS broadcast ephemeris. Implementation of sliding interpolation algorithm for equidistant nodes based on BDS broadcast ephemeris.
Sascha Wilkens. (2019) Computational Challenges for Value-at-Risk and Expected Shortfall: Chebyshev Interpolation to the Rescue?. SSRN Electronic Journal.
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