fluctuations not forecasted by Gaussian models. This paper applies a resampling method based on the bootstrap and a bias …-correction step to improve Value-at-Risk (VaR) forecasting ability of the n-EGARCH (normal EGARCH) model and correct the VaR for both … long and short positions. Our aim is to utilize the advantages of this model, but still use the bootstrap resampling method …

An intensive and still growing body of research focuses on estimating a portfolio’s Value-at-Risk.Depending on both the … orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … proposed estimation approach pairs intuitiveappeal with computational efficiency. We evaluate various alternative estimation …

fifth risk factor based on realized volatility of index returns. Moreover, instead of using data for stocks of a particular … investable equity indices in the period of 2000-2015. Such an approach is proposed to estimate an equity risk premium for a … years we illustrate the importance of model risk and data overfitting effects when drawing conclusions upon results of …

-frequency intraday returns. It disentangles covariance estimation into variance and correlation components. This allows to estimate … covariance estimation and the jump robustness of the estimator are illustrated in a simulation study. In an application to the …

index even after most risk-adjustments, and thereby suggest that the outperformance of the strategy is not merely a … compensation for higher risk. Nevertheless, we also document that the superior returns of the DoD strategy may be largely …