(CAPM) framework. The dynamic of systematic risk across time and frequency is analyzed to investigate stock risk … different asset allocation. We conclude that the standard CAPM assumes short-run investment. Then, investors should consider … time-frequency CAPM to perform systematic risk analysis and portfolio allocation. …

growth and dynamic nature require robust methods for modeling their volatility. The Generalized Auto Regressive Conditional … Heteroskedasticity (GARCH) model is a well-known mathematical tool for predicting volatility. Nonetheless, the Realized-GARCH model has … been particularly under-explored in the literature involving cryptocurrency volatility. This study emphasizes an …

can be used in risk measurement and forecasting. Value at risk (VaR) is a widely used measure of financial risk, which … timelines were used to carry out stressed value at risks, and it was seen that during periods of crisis, the volatility of asset … returns was higher. The other steps that followed examined the relationship of the variables, correlation tests and time …

to its improvement in return density forecasting. Empirical applications to equity data show that several RCOV estimators … consistently perform better than others and emphasize the importance of RCOV selection in covariance modeling and forecasting. …

This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and … performance in forecasting and bootstrapping VaR and ES. Extension of this non-stationary distribution in literature is quite … bulk distribution components. This implies that the combination of a stochastic econometric model with extreme value theory …

-based asset allocation strategy outperforms the three alternatives on many common metrics, including annualized return, volatility …

volatility and models based on the extreme value theory (EVT). ES forecasts were calculated for conditional APARCH models formed …In this study, we use daily gold log-returns to analyse the quality of forecasting expected shortfalls (ES) using … innovations of EVT models allow the improvement of the accuracy of ES forecasting. …