Forward-Looking Stress Testing Under Macro Scenarios: Stable SVaR Estimation Using a Hybrid GPR-HS Framework with SACS
arXiv:2606.07575v1 Announce Type: cross Abstract: Regulatory stress testing frameworks, including the Comprehensive Capital Analysis and Review (CCAR) and the Internal Capital Adequacy Assessment Process (ICAAP), require robust Stressed Value-at-Risk (SVaR) estimation under forward-looking macroeconomic scenarios. Traditional parametric approaches often exhibit numerical instability under extreme shocks, reducing the reliability of capital projections. This paper extends the Hybrid Gaussian Process Regression Historical Simulation (GPR-HS) framework of Vadrevu (2026) to forward-looking stress
The increasing complexity and volatility of global financial markets necessitate more robust and forward-looking stress testing methodologies to prevent systemic shocks, especially with new AI techniques becoming available.
Reliable stress testing and capital projection are critical for financial stability, enabling institutions to accurately assess risk exposure and regulators to enforce effective capital requirements.
This research introduces a more stable and accurate method for Stressed Value-at-Risk (SVaR) estimation under extreme macroeconomic scenarios, enhancing risk management practices beyond traditional parametric models.
- · Financial institutions (risk management departments)
- · Financial regulators
- · Quantitative finance researchers
- · AI/ML model developers in finance
- · Financial institutions relying solely on traditional, less robust stress testing
- · Outdated financial modeling software providers
Improved accuracy in financial stability assessments and capital allocation decisions by financial institutions.
Potentially more resilient financial systems, better equipped to withstand unforeseen economic shocks and crises.
Enhanced trust in the financial sector's ability to self-regulate and respond to an increasingly complex global economic environment.
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Read at arXiv cs.LG