This paper demonstrates how cash outflows due to credit lines can be modeled in a liquidity stress test.
Stress testing and model validation: application of the Bayesian approach to a credit risk portfolio
The authors of this paper develop a Bayesian-based credit risk stress-testing methodology.
This paper analyzes and quantifies the idea of model risk in the environment of internal model building.
Quant ideas paper dissects layers of valuation models for physical assets
Market shocks are earthquakes, not a game of roulette
Avoiding model failure will be a key issue in 2015
"They all fall short," says one expert, as banks try to vet vendor models
Banks struggling to prise information out of vendors after Fed clamps down
Derivatives pricing and expected exposure models must be backtested as a basic regulatory requirement. But what does this mean exactly, and how can it be used to reserve against model risk? Lee Jackson introduces a general backtesting framework for…
Filippo Della Casa and Michele Gaffo propose a new framework to run portfolio optimisation for life insurance business, by exporting the replicating portfolio technique from risk management to investment management. In particular, they develop a new risk…
Stress testing is a vital part of successful risk management, but risk managers at energy trading firms frequently face obstacles in designing and implementing successful stress testing programmes. In this article, Carlos Blanco provides some advice on…
Risk managers need to look beyond models and consider a wider universe of risks, says Reeves
Hedge backtesting for model validation
With the 'London Whale' modelling failures still casting a shadow over the industry, BAML model risk head advocates ongoing testing
Copulas and credit models
Non-linear mixture of asset return models
Models that use factors such as key risk indicators, or KRIs, for inputs align the op risk function with credit risk and market risk - and may increase the effectiveness of operational risk within an organisation. Marcelo Cruz looks at key factors in…
It's nice to see op risk managers becoming more aware of their limitations
Beware of data leverage