Machine learning with kernels for portfolio valuation and risk management

Lotfi Boudabsa () and Damir Filipović ()
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Lotfi Boudabsa: EPFL
Damir Filipović: EPFL

Finance and Stochastics, 2022, vol. 26, issue 2, No 1, 172 pages

Abstract: Abstract We introduce a simulation method for dynamic portfolio valuation and risk management building on machine learning with kernels. We learn the dynamic value process of a portfolio from a finite sample of its cumulative cash flow. The learned value process is given in closed form thanks to a suitable choice of the kernel. We show asymptotic consistency and derive finite-sample error bounds under conditions that are suitable for finance applications. Numerical experiments show good results in large dimensions for a moderate training sample size.

Keywords: Dynamic portfolio valuation; Kernel ridge regression; Learning theory; Reproducing kernel Hilbert space; Portfolio risk management; 68T05; 91G60 (search for similar items in EconPapers)
JEL-codes: C15 G32 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00780-021-00465-4

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