quantile and expectile estimation, a platform for risk assessment is provided. ES and implications for tail events under … different distributional scenarios are investigated, particularly we discuss the implications of increased tail risk for mixture … can be successfully estimated on a daily basis using a one-year time horizon across different risk levels. …

. Based on these active risk factors, an adjustment for intertemporal dependency is made. The authors extend TEDAS methodology … to three gestalts differing in allocation weights’ determination: a Cornish-Fisher Value-at-Risk minimization, Markowitz …

order to apply pricing tools of financial mathematics, one needs to isolate a Gaussian risk factor. A conventional model for … Gaussian variable appears. Earlier work investigated this temperature risk in dfferent locations and showed that neither … accurate fitting procedure of localised temperature risk process by achieving excellent normal risk factors. -- Weather …

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of … Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy … component analysis ; Value-at-Risk …

The simulation of risk processes is a standard procedure for insurance companies. The generation of simulated … (aggregated) claims is vital for the calculation of the amount of loss that may occur. Simulation of risk processes also appears …

In this paper we propose a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the … parameters over the 100 largest US publicly traded financial institutions. We demonstrate the suitability of this risk measure by … comparing the proposed FRM to other measures for systemic risk, such as VIX, SRISK and Google Trends. We find that mutual …

local BOLD signal. Applying a GLM on the DSFM-based time series resulted in a significant correlation between the risk of … decision-related reactions within the DSFM time series predicted individual differences in risk attitudes as modeled with the …