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 …

We define risk spillover as the dependence of a given asset variance on the past covariances and variances of other … assets. Building on this idea, we propose the use of a highly flexible and tractable model to forecast the volatility of an … international equity portfolio. According to the risk management strategy proposed, portfolio risk is seen as a specific combination …

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 …

single intuitive number, defined here as the “crash volatility”, to characterize the true left-tail risk as an alternative to … the usual downside deviation. The crash volatility can be fed into a typical mean-variance optimizer, allowing the … optimizer to finally “see” the risk effect of the non-Gaussian distribution. An example using Amaranth's returns before it lost …

In the literature, there is no consensus as to which Value-at-Risk forecasting model is the best for measuring market … risk in banks. In the study an analysis of Value-at-Risk forecasting model quality over varying economic stability periods …-GARCH(1,1), CAViaR and historical simulation models in periods with contrasting volatility trends (increasing, constantly high …

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 …