reactions to market jumps with implications for portfolio risk management. Employing high-frequency data for the constituents of … to the downside and upside jumps can be mitigated. We contrast the risk exposure of individual stocks with those of the …

We propose and backtest a multivariate Value-at-Risk model for financial returns based on Tukey's g-and-h distribution …-and-h distributed residuals to three European stock indices and provide results of out-of-sample Value-at-Risk backtests. We find that …

quantile and expectile estimation, a platform for risk assessment is provided. ES and implications for tail events under … allow for Expected Shortfall (ES) estimation. Connecting the implied tail thickness of a family of distributions with the … different distributional scenarios are investigated, particularly we discuss the implications of increased tail risk for mixture …

quantile and expectile estimation, a platform for risk assessment is provided. ES and implications for tail events under … allow for Expected Shortfall (ES) estimation. Connecting the implied tail thickness of a family of distributions with the … different distributional scenarios are investigated, particularly we discuss the implications of increased tail risk for mixture …

extreme risk modeling based on full distribution modeling and and extreme value theory …

The recent crisis revived interest in financial transaction taxes (FTTs) as a means to offset negative risk … financial markets as the literature has here-to-fore been focused too narrowly on Gaussian variance as a measure of volatility … price jumps affects not only the performance of many risk-hedging algorithms but directly influences the frequency of …

means that there is scope for further risk reduction by the introduction of new market securities -- financial innovation … equilibria is a novel theory of backward stochastic difference equations (BSΔEs) in discrete time, which we develop in analogy to … the currently incomplete theory of backward stochastic differential equations (BSDEs) in continuous time. The new tool is …

Contemporary financial stochastic programs typically involve a trade-offbetween return and (downside)-risk. Using …. We find that the model can be tuned easily using Value-at-Risk (VaR) related benchmarks. In the multi-stage setting, we … formally prove that the optimal solution consists of a sequence of myopic (single-stage) decisions with risk …