We analyze hedging strategies that minimize tail risk measured by Value-at-Risk (VaR) or Conditional-Value-at-Risk …-switching models. Using cross-hedging examples, we theoretically and empirically demonstrate that tail-risk-minimal strategies can … nonparametric and extreme-value-theory-based methods. These results imply that the proposed methodology for tail risk management can …

and hedging CC options. We study the hedge behaviour and effectiveness for a wide range of models. First, we calibrate … performance is achieved with Delta-Vega hedging in stochastic volatility models. Judging on the calibration and hedging results …

robust with respect to a volatility measure and provide direct policy implications for portfolio composition and hedging. …

Risk management technology applied to high dimensional portfolios needs simple and fast methods for calculation of … Value-at-Risk (VaR). The multivariate normal framework provides a simple off-the-shelf methodology but lacks the heavy … component analysis ; Value-at-Risk …

quantile and expectile estimation, a platform for risk assessment is provided. ES and implications for tail events under … different distributional scenarios are investigated, particularly we discuss the implications of increased tail risk for mixture … can be successfully estimated on a daily basis using a one-year time horizon across different risk levels. …

. Based on these active risk factors, an adjustment for intertemporal dependency is made. The authors extend TEDAS methodology … to three gestalts differing in allocation weights’ determination: a Cornish-Fisher Value-at-Risk minimization, Markowitz …

Equity basket correlation is an important risk factor. It characterizes the strength of linear dependence between … return series, and under the risk neutral measure from option prices. The difference between the two estimates motivates a so … propose several hedging schemes based on implied correlation (IC) forecasts. Modeling IC is a challenging task both in terms …

local BOLD signal. Applying a GLM on the DSFM-based time series resulted in a significant correlation between the risk of … decision-related reactions within the DSFM time series predicted individual differences in risk attitudes as modeled with the …