Technical paper/Value-at-risk (VAR)
Correlation breakdowns, spread positions and central counterparty margin models
The authors investigate correlation behavior during adverse market conditions and the potential impact on CCP margins, finding that such breakdowns appear to be more common than expected.
Volatility-sensitive Bayesian estimation of portfolio value-at-risk and conditional value-at-risk
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
Semi-nonparametric estimation of operational risk capital with extreme loss events
Conditional and unconditional intraday value-at-risk models: an application to high-frequency tick-by-tick exchange-traded fund data
The authors consider conditional and unconditional intraday value-at-risk models for high-frequency exchange-traded funds, providing results useful to practitioners of high-frequency trading.
Credible value-at-risk
This paper proposes a means to determine whether a a calculated VaR is "too large" and give a definition of this term within the context.
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.
Using a skewed exponential power mixture for value-at-risk and conditional value-at-risk forecasts to comply with market risk regulation
The authors investigate a method that combines two skewed exponential power distributions and models the conditional forecasting of VaR and CVaR and is in compliance with the recent Basel framework for market risk.
Value-at-risk models: a systematic review of the literature
The authors conduct a systematic literature review of value-at-risk models to determine which models are most often used and whether any change in model popularity occurred after the 2007-9 financial crisis.
Value-at-risk and the global financial crisis
The authors investigate the forecasting ability of bank VaR estimates around the 2007-9 financial crisis using daily data from seven international banks, finding systemic overstating of VaR either side of the financial crisis and mixed performance during…
Measuring tail operational risk in univariate and multivariate models with extreme losses
The authors consider operational risk models and derive limit behaviors for the value-at-risk and conditional tail expectation of aggregate operational risks in such models.
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.
Deep learning for efficient frontier calculation in finance
The author puts forward a means to calculate the efficient frontier in the Mean-Variance and Mean-CVaR portfolio optimization problems using deep neural network algorithms.
Oil value-at-risk forecasts: a filtered semiparametric approach
This paper proposes the GARCH model combined with the Cornish–Fisher expansion for the oil VaR forecast.
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.
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.
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.
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.