We introduce a multivariate estimator of financial volatility that is based on the theory of Markov chains. The Markov …

The paper studies the impact of the sampling frequency on the volatility of financial time series. We suggest to model … the dependence of volatility on sampling frequency via delay equations for the underlying prices. It appears that these … equations allow to model the price processes with volatility that increases when the sampling rates increase. In addition, these …

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 …

typically observed in measures of financial market volatility in a tractable fashion. The extensions decompose conditional … dependency structure of volatility. This leads to substantial improvements in empirical fit and predictive ability at both short … and long horizons relative to the original REGARCH. A volatility-timing trading strategy shows that capturing volatility …

frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information … content of realized volatility measures extracted from high-frequency data. For this purpose, we introduce asymptotically … exact volatility measurement equations in state space form and propose a Bayesian estimation approach. Our highly efficient …

The estimation of the volatility with high-frequency data is plagued by the presence of microstructure noise, which … integrated volatility but also of the spot volatility; (iii) we show the relevance of the estimator in the prediction of the … variance of the cost of a simulated VWAP execution. Overall we find that, for the integrated volatility, the pre …