The situation of a limited availability of historical data is frequently encountered in portfolio risk estimation …, especially in credit risk estimation. This makes it, for example, difficult to find temporal structures with statistical …-portfolio specific volatility indices called portfolio risk drivers. The dynamics of the risk drivers are modelled by multiplicative …

obtain significantly more data points for the estimation of the respective risk measures. The presented methodology in the α …Weekly, quarterly and yearly risk measures are crucial for risk reporting according to Basel III and Solvency II. For … sufficient in order to estimate Value at Risk and Expected Shortfall sufficiently, given confidence levels of 99.9% and 99 …

This paper extends the procedure developed by Jurado et al. (2015) to allow the estimation of measures of uncertainty …

Sudden and uncertain events often cause cross-contagion of risk among various sectors of the macroeconomy. This paper … introduces the stochastic volatility shock that follows a thick-tailed Student's t-distribution into a high-order approximate … uncertainty risk on macroeconomics. Then, the high-dimensional DSGE model (DSGE-SV-t) is developed to examine the impact of …

the present paper we call such combinations ‘coupled risk measures' and develop a statistical inferential theory for them …Considerable literature has been devoted to developing statistical inferential results for risk measures, especially … a number of risk measures that are of the form of ratios, or even more complex combinations, of two L-functionals. In …

more than a single regime, have performed substantially better than standard methods in terms of volatility and Value-at-Risk …Several procedures to estimate daily risk measures in cryptocurrency markets have been recently proposed in the … forecasting. Three of those procedures are revisited in this paper, and their Value-at-Risk forecasting performance is evaluated …

Beyond their importance from the regulatory policy point of view, Value-at-Risk (VaR) and Expected Shortfall (ES) play … an important role in risk management, portfolio allocation, capital level requirements, trading systems, and hedging … strategies. Unfortunately, due to the curse of dimensionality, their accurate estimation and forecast in large portfolios is …

realized volatility and the augmented GARCH models with the FHS or the EVT quantile estimation methods produce superior VaR …In this paper, we assess the Value at Risk (VaR) prediction accuracy and efficiency of six ARCH-type models, six … realized volatility models and two GARCH models augmented with realized volatility regressors. The α-th quantile of the …