the financial crisis, suggesting that an extreme volatility period requires models that can adapt quickly to turmoil …

Volatility has been used as an indirect means for predicting risk accompanied with an asset. Volatility explains the … variations in returns. Forecasting volatility has been a stimulating problem in the financial systems. This study examined the … different volatility estimators and determined the most efficient volatility estimator. The study described the accuracy of the …

Volatility had been used as an indirect means for predicting risk accompanied with the asset. Volatility explains the … variations in returns. Forecasting volatility had been a stimulating problem in the financial systems. The study examined the … different volatility estimators and determined the efficient volatility estimator. The study described the accuracy of …

There is evidence that volatility forecasting models that use intraday data provide better forecast accuracy as … fills this gap in the literature and extends previous studies on forecasting stock market volatility in several important …, we use forecast horizons ranging from 1 day to 6 months. Third, we evaluate the precision of volatility forecast provided …

Volatility forecasting is crucial for portfolio management, risk management, and pricing of derivative securities …. Still, little is known about the accuracy of volatility forecasts and the horizon of volatility predictability. This paper … volatilities and propose to describe the term structure of volatility predictability by the spot and forward forecast accuracy …

of asset-return volatility, in the context of financial risk management using high frequency data. In our evaluation we … use both statistical criteria (i.e., accuracy of directional volatility predictions) and economic criteria (i … contemporaneous return-volatility relationship and leads to new insights related to linkages between economic and statistical methods …

using recently developed volatility models, including HEAVY, Realized GARCH and GAS models, applied to daily returns on the …

price volatility. To address this issue, we find a phenomenon, "momentum of jumps" (MoJ), that the predictive ability of the … jump component is persistent when forecasting the oil futures market volatility. Specifically, we propose a strategy that … according to their recent past forecasting performance. The volatility data are based on the intraday prices of West Texas …

We study the relationship between conditional quantiles of returns and the long-, medium- and short-term volatility in … the volatility time series provides us with new insights into the pricing of risk and increases the accuracy of our …