Loading...
research article
Machine learning with kernels for portfolio valuation and risk management
November 22, 2021
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.
Type
research article
Web of Science ID
WOS:000721391100001
Authors
Publication date
2021-11-22
Publisher
Published in
Volume
26
Start page
131
End page
172
Subjects
Peer reviewed
REVIEWED
Available on Infoscience
December 4, 2021
Use this identifier to reference this record