forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

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 …

This paper investigates the role of investor attention in forecasting realized volatility for fourteen international … augmented Empirical Similarity model that combines three volatility components, defined over different time horizons, using the … similarity measure between lagged Google search queries and volatility. Results show that investor attention positively affects …

This study employs big data and text data mining techniques to forecast financial market volatility. We incorporate … financial information from online news sources into time series volatility models. We categorize a topic for each news article … volatility. The results of our empirical analysis suggest that the proposed models can contribute to improving forecasting …

The benefits of using flight-to-safety (FTS) in volatility forecasting are assessed within a multivariate GARCH … volatility. Moreover, when comparing with a benchmark and controlling for data snooping, we find that the proposed model yields …

The present study is an attempt to evaluate the predictability of the foreign exchange volatility in thirteen countries …. The data covers the period of 2005-2009. To effectively forecast the volatility in the exchange rates, a GARCH model is … almost all countries except Thailand witnessed non-existence of volatility shocks at least once in a three year pre …

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 …