Modelling
Determination of weights for an optimal credit rating model based on default and nondefault distance maximization
This study proposes a credit rating model that accurately identifies default and nondefault companies by maximizing intergroup credit score deviations and minimizing intragroup deviations.
How accurate is the accuracy ratio in credit risk model validation?
The author presents four methods to estimate the sample variance of the accuracy ratio and the area under the curve.
Body and tail: an automated tail-detecting procedure
The quality of a tail model, which is determined by data from an unknown distribution, depends critically on the subset of data used to model the tail. Based on a suitably weighted mean square error, the authors present a completely automated method that…
Standard errors of risk and performance estimators for serially dependent returns
In this paper, a new method for computing the standard errors (SEs) of returns-based risk and performance estimators for serially dependent returns is developed.
Can CCPs zone in on improved margin buffers?
Dynamically adjusting margin add-ons could reduce cyclical funding demands
Statistical properties of the population stability index
This paper aims to fill a gap in the literature by providing statistical properties of the population stability index (PSI) and some recommendations on its use.
Institutional ETF trading – ETF traders navigate changing conditions
After years of growth and development, exchange-traded funds (ETFs) have cemented their place as a mainstay in investment portfolios and trading strategies. During a year of exceptional volatility and uncertainty, traders were able to take full advantage…
SA-CCR proves a bitter pill for US banks to swallow
Dealers concerned new regime will punish some business lines with rise in risk-weighted assets
A step closer to the perfect volatility model
Research on ‘rough volatility’ gives fresh insight into financial fluctuations, quant expert explains
Model misfires raise questions over training data
Quants wrestle with how far into the past their machine learning models should peer
Regulators’ margin model rules too lax – BlackRock exec
Risk USA: EU anti-procyclicality rules like “putting a curtain over a draughty window”
Covid-19 overwhelmed stress-testing models – banks
Risk USA: lenders forced to apply management overlays to models skewed by macro inputs
Supervisory bank risk early warning modeling: an examiner’s first line of defense
The results of this paper show that robust forward-looking statistical models are superior to backward-looking assessments of supervisory compliance, which could lead to less regulatory burden when integrated into the examination process, particularly at…
Regions deploys early-warning tool for credit risk
Risk USA: system alerted US superregional to impending defaults during Covid crisis
Achieving a holistic view of risk in times of crisis
What happens when risks become too global in scope and increasingly uncertain for a business to manage? Jeroen van Doorsselaere, senior director – finance, risk and regulatory reporting value propositions at Wolters Kluwer, explores the key steps to…
Why the US election fallout was not a surprise to banks
A contested result was unexpected, but scenario planning meant banks weren’t unprepared
Banks fold climate, pandemic and cyber risks into CCAR
OpRisk North America: anchoring idiosyncratic risks to macro scenarios a challenge, say experts
Jerome Kemp on the skewed economics of clearing
Only Fed intervention prevented “a really big market disaster” during Covid, says derivatives veteran
The European intraday electricity market: a modeling based on the Hawkes process
This paper deals with the modeling of trading activity on the European electricity intraday market by a self-exciting point process.
Thinking the unthinkable – Staying ahead of the crisis curve
Industry leaders discuss the increased value of stress-testing in a world rocked by its second financial crisis in 12 years, the likely emergence of non-financial risks, and how financial institutions can establish efficient and effective stress-testing…
Stress‑testing under Covid‑19
Stress‑testing is a challenging exercise to regularly assess a bank’s level of risk or capital adequacy. Olivier Brucker, Sunayana Mehra and Ed Young of Moody’s Analytics explore an approach that can address this, proposing an alternative methodology…
Performance of value-at-risk averaging in the Nordic power futures market
The authors investigate the performance of various value-at-risk (VaR) models in the context of the highly volatile Nordic power futures market, examining whether simple averages of models provide better results than the individual models themselves.
Back to school: BlackRock uses quant quake lessons on Covid
Pandemic prompts a switch in approach from strategic to tactical
Corporate default risk modeling under distressed economic and financial conditions in a developing economy
The authors create stepwise logistic regression models to predict the probability of default for private nonfinancial firms under distressed financial and economic conditions in a developing economy. Their main aim is to identify and interpret the…