a blocked realized kernel estimator, different smoothing windows, various regularization methods and two forecasting … studies have shown and translate into substantial utility gains from the perspective of an investor with pronounced risk …

This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time … results are robust to using different time-series models, time periods, asset classes, and risk measures. …

The paper develops a tail risk forecasting model that incorporates the wealth of economic and financial information … available to risk managers. The approach can be viewed as a regularized extension of the two-stage GARCH-EVT model of McNeil and … extreme value distribution of risk. We use a rich data set from the US equity market to explore when this additional …

We introduce a new class of momentum strategies, the risk-adjusted time series momentum (RAMOM) strategies, which are … how these volatility measures can be used for risk management. We find that momentum risk management significantly … increases Sharpe ratios, but at the same time may lead to more pronounced negative skewness and tail risk. Furthermore, momentum …