When analysing the volatility related to high frequency financial data, mostly non-parametric approaches based on … stochastic volatility. Estimation of the model delivers measures of daily variation outperforming their non …

Bayesian forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of … volatility components. From a practical point of view, ML also becomes computationally unfeasible for large numbers of components … forecasts which in principle is applicable for any continuous distribution with any number of volatility components. Monte Carlo …

forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of volatility … which in principle is applicable for any continuous distribution with any number of volatility components. Monte Carlo … linear compared to optimal forecasts is small. Extending the number of volatility components beyond what is feasible with MLE …

This paper analyzes the impacts of news shocks on macroeconomic volatility. Whereas in any purely forward-looking model …, such as the baseline New Keynesian model, anticipation amplifies volatility, we obtain ambiguous results when including a …) to provide numerical evidence that news shocks increase the volatility of key macroeconomic variables in the euro area …

may be generalized, if we use alternative measures of volatility. We choose one feasible alternative and derive a … generalized volatility model. Applying this model to some exemplary market indices, we are able to give some empirical evidence …

This paper focuses on the extraction of volatility of financial returns. The volatility process is modeled as a … the volatility is not observable, the logarithm of the daily high-low range is employed as its proxy. The estimation of … parameters and volatility extraction are performed using a modified version of the Kalman filter which takes into account the …

on some high frequency basis has spurred the research in the field of volatility modeling and forecasting into new … directions. First, the realized variance is a much better estimate of the latent volatility than the sum of the weighted daily … squared returns. As such it is better suited for comparing the out-of-sample performances of competing volatility models …