in order to account for risk reduction through hedging. Results allow us to conclude that: dynamic hedging strategies …

specification, in the forecasting of multi-period Value-at-Risk (VaR) and Expected Shortfall (ES) across 20 stock indices worldwide … forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

Predicting volatility is a must in the finance domain. Estimations of volatility, along with the central tendency … assignment of diversifying assets in order to form efficient portfolios with a higher risk to reward ratio. The objective of this … research is to analyze the influence of COVID-19 on the return and volatility of the stock market indices of the top 10 …

in modern financial risk management techniques like Value at Risk. This paper suggests a regression based density …

This paper evaluates the profitability of applying four different volatility forecasting models to the trading of … applied in this paper are: historical volatility, two ARCH models, and an autoregressive model for the volatility index. VDAX …. The ARCH models perform best in generating profits for market makers. Forecasts based on historical volatility also …

The adjusted measure of realized volatility suggested in [20] is applied to high- frequency orderbook and transaction … data of DAX and BUND futures from EU- REX in order to identify the drivers of intraday volatility. Four components are … realized volatility can be predicted by a simple linear model based on the components identified. It is shown how the …