Value at risk (VaR) has become a standard measure of portfolio risk over the last decade. It even became one of the … corner stones in the Basel II accord about banks' equity requirements. Nevertheless, the practical application of the VaR … concept suffers from two problems: how to estimate VaR and how to optimize a portfolio for a given level of VaR? For the first …

performs relatively best in term of MSPE, followed by GARCH, Risk metrics and historical volatility. In terms of VaR, we test … that VaR forecasts at 90 % and 95% have desirable properties. Regarding 99% VaR forecasts, We find significant evidence …

This paper proposes a method for estimating the VaR of a portfolio based on copula and extreme value theory. Each …

, when we calculate a VaR (Value at Risk) with an instantaneous volatility to check the prediction performance. Furthermore …

This paper examines different multivariate models to evaluate what are the main determinants when doing VaR forecasts … and the time sample used for VaR backtesting. The calculated VaR values are then compared using three different testing …

Value at risk (VaR) has become a standard measure of portfolio risk over the last decade. It even became one of the … corner stones in the Basel II accord about banks' equity requirements. Nevertheless, the practical application of the VaR … concept suffers from two problems: how to estimate VaR and how to optimize a portfolio for a given level of VaR? For the first …

evolutionary game theory of a financial market, where part of the investors use the VaR technique to manage their risk. We study …

evolutionary game theory of a financial market, where part of the investors use the VaR technique to manage their risk. We study …

questions have been answered using the literature review methodology. The VAR model is constructed to evaluate the relation … between the REIT market and macroeconomic factors. Ultimately, downside risk of REIT market is assessed by the GARCH(1,1)-VaR …

at Risk (VaR) calculation entails a numerically indirectprocedure. The Quantile Regression (QR) estimation is an …-KF) based on the QR approach thatcan be used to obtain robust SV model parameter estimates as well as VaR estimates. TheRQMM is … existing Nonlinear Filtering (NF) scheme.This approach is used in likelihood and VaR computations. This algorithm provides …