We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high … lower cost in capital reserves. In ES estimation the hybrid model yields the smallest error statistics surpassing even the …

has roots in fundamentals. Higher market risk predicts greater idiosyncratic earnings volatility as well as dispersion and …From 1963 through 2015, idiosyncratic risk (IR) is high when market risk (MR) is high. We show that the positive …

A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive … in applications in this context. This study reviews the different volatility models and points out their advantages and …

builds distribution risk into a real business cycle model, hypotheses on the determinants of the relative volatility of …Weakening bargaining power of unions and the increasing integration of the world economy may affect the volatility of … capital and labor incomes. This paper documents and explains changes in income volatility. Using a theoretical framework which …

making and risk management. Over the past three decades there has been a trend towards increased asset return correlations … return correlations using weekly returns on futures markets and investigate the extent to which multivariate volatility … models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how …

relatively low market volatility may have unintended consequences for banks' risk exposure … risk include an additional stress component introduced by the recent Basel 2.5 regulation. Our optimization with the Basel …

management. Evaluation of volatility models is then considered and a simple Value-at-Risk (VaR) diagnostic test is proposed for …This paper considers the problem of model uncertainty in the case of multi-asset volatility models and discusses the … use of model averaging techniques as a way of dealing with the risk of inadvertently using false models in portfolio …

(systemic) risks. Forecasts are obtained from: (a) autoregressive and factor-augmented VARs with linear GARCH volatility (FAVARs … the period 1972:1-2014:12 to forecasts our tail risk indicators with each model in pseudo-real time. Our key finding is …

ten sectoral indices over the period January 1997-Febraury 2014. The estimation of a bivariate VAR-GARCH-in-mean model … suggests that oil price volatility affects stock returns positively during periods characterised by demand-side shocks in all …

during the period of the financial crisis. In a Value-at-Risk (VaR) analysis, finally, we further illustrate the advantages … confidence levels while other models fail to specify the risk correctly. This analysis shows that ignoring the actual nature of … dependence might lead to an underestimation of the risk for portfolios combining EUAs with commodities or equity investments …