arXiv research

Chebyshev technique reduces FRTB-IMA equity autocallables computation costs by 90%.

Facing the FRTB, banks need to allocate their capital to each business units or risk positions to evaluate the capital efficiency of their strategies. This paper proposes two computationally efficient allocation methods which are weighted according to liquidity horizon. Both methods provide more stable and less negativ…

In this paper we introduce a new technique based on high-dimensional Chebyshev Tensors that we call \emph{Orthogonal Chebyshev Sliding Technique}. We implemented this technique inside the systems of a tier-one bank, and used it to approximate Front Office pricing functions in order to reduce the substantial computation…

This work reviews and tests risk allocation strategies in finance, highlighting Shapley allocation's advantages.

Financial institutions now face the important challenge of having to do multiple portfolio revaluations for their risk computation. The list is almost endless: from XVAs to FRTB, stress testing programs, etc. These computations require from several hundred up to a few million revaluations. The cost of implementing thes…

New SigSwap model for path-dependent financial risk.

Unified RMOT framework for non-modelable risk factors reduces audit bounds.

Under the Fundamental Review of the Trading Book (FRTB) capital charges for the trading book are based on the coherent expected shortfall (ES) risk measure, which show greater sensitivity to tail risk. In this paper it is argued that backtesting of expected shortfall - or the trading book model from which it is calcula…

An Ensemble Anomaly Detection Framework for Risk Calculation Integrity

Differential ML combines AAD with ML for fast, accurate financial derivatives pricing and risk management.

SHARC explains machine learning risk models for regulatory capital, linking outputs to scenarios.