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 …

with Sharpe's ratio, offering an approach to point and confidence interval estimation which employs bootstrap resampling …The Sharpe ratio is a common financial performance measure that represents the optimal risk versus return of an … issues surrounding its statistical properties. Given the importance of obtaining robust determinations of risk versus return …

irrelevant for stocks with extremely high risk. This study finds that the SAI in India explains the variation in the excess …