Performance-Enhancing Market Risk Calculation Through Gaussian Process Regression and Multi-Fidelity Modeling
The market risk measurement of a trading portfolio in banks, specifically the practical implementation of the value-at-risk (VaR) and expected shortfall (ES) models, involves intensive recalls of the pricing engine. Machine learning algorithms may offer a solution to this challenge. In this study, w...
Saved in:
| Main Authors: | N. Lehdili, P. Oswald, H. D. Nguyen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
|
| Series: | Computation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3197/13/6/134 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Leveraging Bayesian Quadrature for Accurate and Fast Credit Valuation Adjustment Calculations
by: Noureddine Lehdili, et al.
Published: (2024-11-01) -
Option Pricing Models: A Study of the Black-Scholes-Merton Model
by: Xue Kexuan
Published: (2025-01-01) -
BALANCED MODEL OF EXCHANGE OPTION PRICE
by: Vladimir A. Galanov
Published: (2017-09-01) -
PRICING OF THE ASIAN OPTION WITH THE KAMRAD-RITCHKEN’S TRINOMIAL MODEL
by: Jihan Nabila Wafa’, et al.
Published: (2025-07-01) -
Influence of stochastic volatility for option pricing
by: Akvilina Valaitytė, et al.
Published: (2004-12-01)