Expected shortfall
A study of China’s financial market risks in the context of Covid-19, based on a rolling generalized autoregressive score model using the asymmetric Laplace distribution
The authors construct a risk measurement model for the financial market during the Covid-19 pandemic, using data from the Shanghai Stock Exchange for empirical analysis.
Party’s over as more banks drop internal models for market risk
At least three systemic banks in Europe intend to ditch IMA for capital requirements
Realized quantity extended conditional autoregressive value-at-risk models
The author presents models for improved Value-at-Risk forecasts and joint forecasts of Value at Risk and Expected Shortfall and demonstrates that high-frequency-data-based realized quantities lead to better forecasts.
Filling the gaps in Basel’s interest rate risk measures
Reverse stress-testing or VAR may work better than existing outlier tests, but are hard to manage
As banks limit FRTB model use, outputs get more volatile
Risk managers say selection of stress window becomes more sensitive if fewer desks are on IMA
EU banks balk at new market risk models back test
EBA proposals introduce additional expected shortfall back test for market capital risk models under FRTB
EU banks fear Brexit battle over FRTB internal models
Bank of England approach looks easier, but that may not make much difference to model uptake
Banks find new uses for discarded FRTB models
Much-maligned IMA models are being upcycled and repurposed for internal risk management
Asymmetric risk spillovers between oil and the Chinese stock market: a Beta-skew-t-EGARCH-EVT-copula approach
The author uses the marginal expected shortfall method alongside the Beta-skew-t-exponential generalized autoregressive conditional heteroscedasticity-extreme value theory model and the CoVaR model to investigate risk spillover between the crude oil…
Semiparametric GARCH models with long memory applied to value-at-risk and expected shortfall
The authors introduce and apply new semiparametric GARCH models with long memory to obtain rolling one-step ahead forecasts for the value-at-risk and expected shortfall (ES) for market risk assets.
Modeling very large losses. II
This paper presents a means to estimate very large losses by supposing the event is the result of a succession of factors and estimating the probability of each factor.
Counterparty risk allocation
This paper investigates the problem of minimizing the risk of exposure to a small number of defaultable counterparties based on spectral risk measures.
Regulators should be careful what they wish for on FRTB
New framework likely to reduce use of internal models, as planned; but is that a good thing?
Expected shortfall model based on a neural network
This paper presents a model that combines ES models based on EVT and neural networks and meets all criteria for the validity of the Basel III standard.
EU banks fear outlier status on non-modellable risk charges
Dealers face disadvantage if EU implements more granular and costly version of FRTB than US, UK
Podcast: Matthew Dixon on decomposition of portfolio risk
New approach calculates contributions to value-at-risk for nonlinear portfolios
Central counterparty capital and nondefault losses
This paper analyses the components of central counterparty (CCP) capital requirements and makes several observations on the potential for loss absorption.
Does regulators’ favourite climate risk metric measure up?
FSB and Basel Committee back climate VAR, but practitioners will take some convincing
FRTB starts ‘tug of war’ between front and back offices
Risk USA: dealers face trade-off between accuracy of pricing models and level of capital charges
Systemic risk of the Chinese stock market based on the mobility measures of the marginal expected shortfall
This paper applies the dynamic mixture copula model method and proposes a mobility measure of the marginal expected shortfall to depict the changing systemic risk in China’s mainland stock market and Hong Kong’s stock market.
A simple and robust approach for expected shortfall estimation
This paper proposes a simple and robust expected shortfall estimation method based on the tail-based normal approximation.