using volatility impulse response analysis. The data set features ten years of daily returns series for the New York Stock … independent shocks on volatility through time, while avoiding typical orthogonalization and ordering problems. Volatility impulse … response functions (VIRF) provide information about the impact of independent shocks on volatility. HHś VIRF extends a …

Availability of high frequency data has improved the capability of computing volatility in an efficient way …. Nevertheless, measuring volatility/covariance from the observation of the asset price is challenging for two main reasons: observed … multivariate volatility, with particular focus on using high frequency data. Exploiting the fact that the method allows to compute …

This paper proposes a new class of multivariate volatility model that utilising high-frequency data. We call this model …

volatility of individual stock returns and exchange rate returns. …

dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model … volatility forecasting of stock returns and exchange rates. …

This paper shows that combinations of option implied and time series volatility forecasts that are conditional on … that this method works well in practice by applying it to volatility forecasts for the Mexican Peso-US Dollar exchange rate …, where the actual value is taken to be the realized volatility measured using intra-day observations …

We propose using the Realized GARCH model to estimate the daily price volatility in the EPEX power markets. The model … specification extracts the volatility-related information from realized measures, which substantially improves the in-sample fit of … that intra-day range is an effective volatility indicator in the power market as the benefit of including intra-day range …