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 …

-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 …

situations it is better to renounce parameter estimation altogether and pursue some trivial strategy such as the totally risk …In the present work, I derive the risk functions of 5 standard estimators for expected asset returns which are …-variance estimator, and the CAPM estimator. I resolve the question why it is meaningful to study the risk function in the context of …

situations it is better to renounce parameter estimation altogether and pursue some trivial strategy such as the totally risk … ; Naive diversification ; Out-ofsample performance ; Risk function ; Shrinkage estimation …In the present work I derive the risk functions of 5 standard estimators for expected asset returns which are …