Value-at-risk (VAR)
The importance of window size: a study on the required window size for optimal-quality market risk models
In this paper the authors study different moving-window lengths for value-at-risk evaluation, and also address subjectivity in choosing the window size by testing change point detection algorithms.
US unit of Barclays close to a VAR breach in Q4
Largest loss-to-VAR ratio at the firm was highest among 10 US intermediate holding companies
Estimating value-at-risk using quantile regression and implied volatilities
In this paper the authors propose a semi-parametric, parsimonious value-at-risk forecasting model based on quantile regression and readily available market prices of option contracts from the over-the-counter foreign exchange interbank market.
StanChart reports first VAR breach since Q2 2020
Three exceptions recorded in the fourth quarter put the bank one step away from a higher capital requirement
FRTB capital quirk for sovereign bonds bewilders banks
EU treatment of govvies under internal models is worse than standardised approaches
Top US banks record 14 VAR breaches
JPM, Morgan Stanley, BofA, Citi, Goldman and State Street wrong-footed in volatile end to 2021
JP Morgan incurs eight VAR breaches, triggering capital hike
Largest trading loss in Q4 reached 207% of the bank’s VAR limit
SocGen cut trading VAR by a third in Q4
Trading risk gauge shrinks to lowest in 17 years
Evaluation of backtesting on risk models based on data envelopment analysis
In this study, different value-at-risk models, which are used to measure market risk, are analyzed under different estimation approaches and backtested with an alternative strategy.
Modeling multivariate operational losses via copula-based distributions with g-and-h marginals
In this paper, the authors propose a family of copula-based multivariate distributions with g-and-h marginals.
Nordea’s trading VAR keeps climbing amid rate hike jitters
Trading risk gauge surged 17% through Q4
ING’s interest rate VAR spiked in Q4
Potential-loss indicator for rates trading peaked at €20 million
UBS incurred a VAR breach in Q4
The latest larger-than-expected loss – the fourth in 2021 – leaves the bank one step closer to higher capital requirements
Estimating future value-at-risk from value samples, and applications to future initial margin
This paper discusses several methods to estimate fVaR or margin requirements and their expected time evolution, from simple options to more complex interest swaps.
Bank of America’s VAR drops 19% in Q4
Average one-day trading VAR falls to lowest point since Q1 2020
Buy side turns to extreme value theory to spot tail risks
Asset managers reappraise decades-old technique to gauge downside risks amid fears of volatile 2022
Podcast: Matthew Dixon on decomposition of portfolio risk
New approach calculates contributions to value-at-risk for nonlinear portfolios
Nonlinear risk decomposition for any type of fund
A risk decomposition by fund manager, factor or instrument is proposed
CME delays Span 2 rollout till at least mid-2022
FCMs ask bourse to postpone long-planned switch to new VAR model to allow more time for testing
JP Morgan, Goldman lead US banks in cutting VAR-based charges
On aggregate, requirements connected to commodity positions fell the most, down 28% from end-June
US unit of TD Group close to a VAR breach in Q3
Largest loss-to-VAR ratio at the firm was highest among 10 US intermediate holding companies
Does regulators’ favourite climate risk metric measure up?
FSB and Basel Committee back climate VAR, but practitioners will take some convincing
Extreme value theory for operational risk in insurance: a case study
This study aims to test the sufficiency of the solvency capital requirement approach for calculating operational risk using the standard formula as defined in Solvency II.
Evaluation of backtesting techniques on risk models with different horizons
In this study different value-at-risk (VaR) models are analyzed under different estimation approaches (filtered historical simulation, extreme value theory and Monte Carlo simulation) and backtested with different techniques.