For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between … futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers … that the new method based on stochastic volatility models with the asymmetry and long memory outperforms the forecasting …

forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures … outperform existing dynamic conditional correlation models for forecasting future covariances. Among the new fMSV models, the … Cholesky MSV model with long memory and asymmetry shows stable and better forecasting performance for one-day, five-day and ten …

The paper investigates the impact of jumps in forecasting co-volatility, accommodating leverage effects. We modify the … definite. Using this approach we can disentangle the estimates of the integrated co-volatility matrix and jump variations from … the co-jumps of two assets have a significant impact on future co-volatility, but that the impact is negligible for …

forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that …We document the forecasting gains achieved by incorporating measures of signed, finite and infinite jumps in …, 60, and 300 seconds), forecast horizons (1, 5, 22, and 66 days) and the use of standard and robust-to-noise volatility …

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 …

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 …

variations in returns. Forecasting volatility has been a stimulating problem in the financial systems. This study examined the … forecasting technique with respect to various volatility estimators. The methodology of volatility estimation included Close … measuring parameters like ME, RMSE, MAE, MPE, MAPE, MASE, and ACF1 gave the accuracy of forecasting with the best volatility …

We study the empirical properties of realized volatility of the E-mini S&P 500 futures contract at various time scales …, ranging from a few minutes to one day. Our main finding is that intraday volatility is remarkably rough and persistent. What … is more, by further studying daily realized volatility measures of close to two thousand individual US equities, we find …

We propose the use of a risk measure built on flight-to-safety (FTS) episodes into a volatility forecasting model. We …. Superior model performance is found over some of the most common volatility forecasting models proposed in the literature that … bond and gold markets. By allowing each FTS day to be an indicator of higher future volatility, we document statistically …