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 …

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 …

investigate risk/return characteristics of fundamentally-weighted and market-cap-weighted indexes and employ various risk …-adjustment approaches to ensure that return differences are not driven by risk. Based on stocks in the DJ Stoxx 600 index from July 1993 to … April 2007, we show that fundamentally-weighted indexes achieve higher risk-adjusted returns than market …

. These RV budgets provide insight into the risk concentration of a portfolio. Furthermore, the RV budgets can be directly … used in a portfolio strategy, called the equal-risk-contribution allocation strategy. This yields both a higher average …