Forecasts of asset return volatility are necessary for many financial applications, including portfolio allocation …. Traditionally, the parameters of econometric models used to generate volatility forecasts are estimated in a statistical setting and … paper investigates the economic benefit of direct utility based estimation of the parameters of a volatility model and …

analyze empirical results for a selection of existing realized measures of volatility and incorporate them in a Realized GARCH … framework for the joint modeling of returns and realized measures of volatility. An influential bias in these measures is … over time, which stresses the importance of careful modeling and forecasting of volatility. We show that improved model fit …

. When new information arrives, the market's expectations change. Therefore, prices fluctuate. Thus, price volatility is due … to information arrivals and hence, volatility can be forecast, based on the up-to-date information. However, when the … frame work to study risk and return, so that, we can gain a better understanding of market volatility. …

We observe from the late 1990s an increasing phenomenon of volatility on these following markets: Oil (WTI price … of volatility and overcoming its first definition of risk measure, we have evaluated their interdependencies from a VAR … trajectories from FIGARCH model. This paper is presented as follows: Section 1 opens on a definition of the volatility, Section 2 …

penalised through higher capital charges. This paper investigates the performance of five popular volatility models that can be …

VaR forecasts of a set of conditional volatility models. This risk management strategy is GFC-robust in the sense that …