-at-Risk (VaR) and ES. We provide explicit expressions for the additional terms in the asymptotic covariance matrix that result from … application to VaR and ES forecasts for daily FTSE 100 index returns as generated by AR-GARCH, AR-GJR-GARCH, and AR-HEAVY models …

Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled … oflow probability worst outcomes, RiskMetrics analysis underpredicts the VaR while historical simulationoverpredicts the VaR …. However, the estimates obtained from applying the semi-parametric method aremore accurate in the VaR prediction. In addition …

from the total portfolio’s VaR, there is agrowing need for information about (i) the marginal contribution of the … individual portfolio components tothe diversified portfolio VaR, (ii) the proportion of the diversified portfolio VaR that can be … attributed toeach of the individual components consituting the portfolio, and (iii) the incremental effect on VaR ofadding a new …

to measure Value-at-Risk (VaR). The risk estimates of these models are used to determine capital requirements and … estimated VaR. In this paper we define risk management in terms of choosing sensibly from a variety of risk models, discuss the … practices, forecasting VaR and daily capital charges, and discuss alternative policy recommendations, especially in light of the …

shifting the quantitative risk metrics system from Value-at-Risk (VaR) to Expected Shortfall (ES). The Basel Committee on … Banking Supervision (2013, p. 3) noted that: "a number of weaknesses have been identified with using VaR for determining … function that is adopted (ES versus VaR); and (2) their estimated counterparts. The latter is dependent on what models are used …