dynamic factor and a vector autoregressive model and includes stochastic volatility, denoted by FAVAR-SV. Next, a Bayesian … momentum strategy. The estimation of this modeling and strategy approach can be done using an extended and modified version of … risk features like volatility and largest loss, which indicates that complete densities provide useful information for risk. …

This paper introduces the Markov-Switching Multifractal Duration (MSMD) model by adapting the MSM stochastic volatility … feature of durations generated by the MSMD process propagates to counts and realized volatility. We employ a quasi … asymptotic normality for general MSMD specifications. We show that the Whittle estimation is a computationally simple and fast …

We show that realized volatility, especially the realized volatility of financial sector stock returns, has strong …, most importantly, can be exploited in real time. Current realized volatility has the most information content on the … volatility is low, the predicted distribution of returns is less dispersed and probabilistic forecasts are sharper. Given this …

With the recent availability of high-frequency financial data the long range dependence of volatility regained … researchers' interest and has lead to the consideration of long memory models for realized volatility. The long range diagnosis of … volatility, however, is usually stated for long sample periods, while for small sample sizes, such as e.g. one year, the …

issues at high frequency aggregation. We detect jumps through four different methods that encompass constant volatility, time …-varying volatility and periodicity. Our forecasting model is a logistic model adjusted to rare events. At an average 2-minute trading …

In the past decade, the popularity of realized measures and various linear models for volatility forecasting has … the ongoing debate with a comprehensive evaluation of multiple-step-ahead volatility forecasts of energy markets using … commonly used to forecast realized volatility, this paper also contributes to the literature by coupling realized measures with …

nonstationary. We also establish the estimation theory and asymptotic properties for these models in the short horizon and long …