Modelling
A verification model to capture option risk and hedging based on a modified underlying beta
This paper analyzes the relationship between option risk and expected return from the perspective of the underlying beta, and estimates the degree of correlation.
The impact of energy costs on industrial performance: identifying price and quantity effects in the aluminum industry using a data envelopment analysis approach
The authors build a frontier function model with technical and cost efficiency measures to assess the impact of energy costs on competitiveness in the aluminum industry, a heavy energy consumer, by identifying what may be attributed to price and quantity…
My kingdom for the right copula
Copulas can still deliver if chosen with due attention to intuition and data, says quant fund chair
Ex-SunGard chief Cris Conde’s random walk to fintech and beyond
Technologist talks artificial intelligence, angel investing and accidentally contributing to the Basel framework
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.
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
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
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…
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.
Science friction: some tire of waiting for quantum’s leap
Use cases for new tech are piling up – from CVA to VAR. But so are the obstacles
A joint model of failures and credit ratings
The authors propose a novel framework for credit risk modeling, where default or failure information and rating or expert information are jointly incorporated in the model.
Banks aim to close op risk stress test capital gap
Standardising stress drivers could help smooth differences between bank loss estimates