Forward-Looking Stress Testing Under Macro Scenarios: Stable SVaR Estimation Using a Hybrid GPR-HS Framework with SACS
Researchers have developed a new framework for estimating Stressed Value-at-Risk (SVaR) in financial risk management. This hybrid Gaussian Process Regression Historical Simulation (GPR-HS) approach, enhanced with Scenario-Averaged Covariance Stabilization (SACS), aims to provide stable and reliable SVaR estimations under forward-looking macroeconomic scenarios. The framework demonstrated consistent convergence across various assets and scenarios, preserving key risk properties and offering a regulator-aligned method for applications like CCAR and ICAAP. AI
IMPACT Provides a more stable and reliable method for financial institutions to assess risk under various economic conditions.