Technical paper/Value-at-risk (VAR)
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.
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.
Nonlinear risk decomposition for any type of fund
A risk decomposition by fund manager, factor or instrument is proposed
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.
The value-at-risk of time-series momentum and contrarian trading strategies
This paper not only provides a theoretical model for the value-at-risk of active and passive trading strategies but also discusses the substantial implications relevant to risk management.
The Fundamental Review of the Trading Book and fat tails
Conservative capital buffers may not be enough to protect against tail events
Risk measures: a generalization from the univariate to the matrix-variate
This paper develops a method for estimating value-at-risk and conditional value-at-risk when the underlying risk factors follow a beta distribution in a univariate and a matrix-variate setting.
Measurement of operational risk regulatory capital in the banking sector: developed countries versus emerging markets
This paper addresses operational risk as a fundamental risk type faced by banks in emerging and developed economies.
Bias-corrected estimators for the Vasicek model: an application in risk measure estimation
The author evaluates the usefulness of bias-correction methods in enhancing the Vasicek model for market risk and counterparty risk management practices.
Machine learning hedge strategy with deep Gaussian process regression
An optimal hedging strategy for options in discrete time using a reinforcement learning technique
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.
Volatility spillover along the supply chains: a network analysis on economic links
The analysis in this paper reveals that additional fundamental risk gets transferred along supply chains, and that suppliers are exposed to additional fundamental risk that is not captured by their market beta. Suppliers are therefore exposed to…
Old-fashioned parametric models are still the best: a comparison of value-at-risk approaches in several volatility states
The authors present backtesting results for 1% and 2.5% VaR of six indexes from emerging and developed countries using several of the best-known VaR models, including generalized autoregressive conditional heteroscedasticity (GARCH), extreme value theory…
An empirical evaluation of large dynamic covariance models in portfolio value-at-risk estimation
This research develops a framework adopting conditional covariance modeling combined with various de-noising methods to estimate the portfolio VaR and proves the importance of DCC over the sample rolling method widely used in the industry.
Value-at-risk in the European energy market: a comparison of parametric, historical simulation and quantile regression value-at-risk
This paper examines a set of value-at-risk (VaR) models and their ability to appropriately describe and capture price-change risk in the European energy market.
Estimation of value-at-risk for conduct risk losses using pseudo-marginal Markov chain Monte Carlo
The authors propose a model for conduct risk losses, in which conduct risk losses are characterized by having a small number of extremely large losses (perhaps only one) with more numerous smaller losses.
Measuring expected shortfall under semi-parametric expected shortfall approaches: a case study of selected Southern European/Mediterranean countries
In this paper, the authors investigate the applicability of semi-parametric approaches for estimating expected shortfall.
Backtesting expected shortfall: a simple recipe?
In this paper, the authors introduce a new ES backtesting framework based on the duality between coherent risk measures and scale-invariant performance measures.
A triptych approach for reverse stress testing of complex portfolios
Pascal Traccucci et al present an extended reverse stress test triptych approach with three variables
A study on window-size selection for threshold and bootstrap value-at-risk models
This paper investigates the effects of window-size selection on various models for value-at-risk (VaR) forecasting using high-performance computing.
Static and dynamic risk capital allocations with the Euler rule
This paper studies the volatility of the Euler rule for capital allocation in static and dynamic empirical applications with a simulated history.
Forecasting value-at-risk
Alvin Stroyny and Tim Wilding build a dynamic risk framework for multi-asset global portfolios