Fundamanetal review of the trading book (FRTB)

https://www.bis.org/publ/bcbs265.htm

MAR30-33 - Calculation of RWA for market risk

https://www.bis.org/basel_framework/standard/MAR?tldate=20240128

Value at risk (VaR) and expected shortfall (ES) risk measures lie at the heart of the market risk capital calculations. Banks that are subject to the market risk rule and/or Basel accords need to estimate and report these risk measures on a daily basis. There are a number of parametric, semi-parametric, and non-parametric estimators that can be utilized for VaR and ES estimation.

The nonparametric estimators of VaR and ES have large asymptotic variance relative to the optimal parametric estimators that can be constructed when the shape of the underlying distribution can be accurately modeled. This brings the modeler to a statistical dilemma - use a nonparametric estimator and pay a high cost of having large confidence intervals or take some model risk and work with significantly tighter confidence intervals provided by the fitted model. The non-parametric estimators (such as sample VaR) are commonly used by the practitioners. We will present robust semi-parametric VaR and ES estimators that outperform the standard ones. These estimators will lead to more stable market risk capital calculations.

In the final part of this project we will perform ES backtesting using traffic light test and Acerbi-Szekely tests (conditional and unconditional versions).