The interest in forecasting the Value at Risk (VaR) has been growing over the last two
decades, due to the practical relevance of this risk measure for financial and insurance …

One of the key components of financial risk management is risk measurement. This typically
requires modeling, estimating and forecasting tail-related quantities of the asset returns' …

Trading algorithms adopt automated risk management systems in order to mitigate against
market risk and extreme market events. These systems are aimed at reducing potential …

The Value-at-Risk (VaR) is a widely used instrument in financial risk management. The
question of estimating the VaR of loss return distributions at extreme levels is an important …

We propose a new framework exploiting realized measures of volatility to estimate and
forecast extreme quantiles. Our realized extreme quantile (REQ) combines quantile …

Purpose This study aims to forecast daily value-at-risk (VaR) for international stock indices
by using the conditional extreme value theory (EVT) with the Realized GARCH (RGARCH) …

We propose a family of range-based risk measures to generalize the role of value at risk
(VaR) in the formulation of range value at risk (RVaR) considering other risk measures …

在金融市场中, 极端事件往往会对投资者造成较大的损失, 建立有效的极端值模型可以降低极端
风险对投资者产生的影响. 本文考虑了极端尾部风险的情况, 基于极值理论和SGEL 分布, 将POT …

Purpose This study aims to implement a novel approach of using the Realized generalized
autoregressive conditional heteroskedasticity (GARCH) model within the conditional …

Purpose This paper aims to focus on a better model to capture the trait of varying volatility in
various financial time series, as well as to obtain reliable estimate of value at risk (VaR) …