an approach to model spot prices that combines mean-reversion, spikes and stochastic volatility. Thereby we use different …

introduce a more realistic assumption incorporating conditional heteroskedasticity. This involves the work on temporal … aggregation of GARCH processes of Drost and Nijman (1993). Using Swedish data, our estimation method produces an overall larger …

Current models for predicting volatility do not incorporate information flow and are solely based on historical … predictor of its stock volatility. The results show that future stock volatility is better predicted by our method than the … flow or as an active source for new information influencing future volatility. Our data suggest that semantic content may …

the stock market volatility is compared in both the Anglophone world and the Sinophone world. I find that the stock market … volatility and the number of publicly available global news stories are strongly linked to each other in both languages …. Contemporaneous correlations between news and volatility are positive and highly significant, and regressions tell us that the …

This paper addresses stock market volatility in Germany between 1991 and 2018. Through a GARCH model with leverage term …, an estimation of volatility in the DAX is provided. Such estimation is then plugged into a quantile regression model … where potential economic determinants are analyzed. The results suggest that stock market volatility in Germany reached its …

The aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets. We … suggest use of the principal component methodology of Stock and Watson (2002) for the stochastic volatility factor model …

seasonal pattern for the conditional volatility for the Swedish stock market has been found. The daily turnover in the Swedish … stock market has an impact on and eliminates to some extent seasonal patterns in conditional volatility. The daily turnover … returns will display a GARCH-pattern of behaviour if the number of trades on the stock market during a day are serially …

informativeness of volatility forecasts produced by ARCH models versus the volatility forecasts derived from option prices and in … improving volatility forecasts produced by ARCH and option models and combinations of models. Daily and monthly data are … $t – 1$ relative to the recent past, then option-implied volatility is much more important than ARCH for forecasting …