obtained from discrete time models by comparing them with high-frequency ex post estimates (e.g. realised volatility) based on … continuous time theory. In explanatory financial variability modelling this raises several methodological and practical issues … illustration provides an example of where an explanatory model outperforms realised volatility ex post. -- Financial variability …

the volatility for over hundred countries around the world. We used the monthly political risk data from the International … governance. Further monthly volatility is constructed from the daily exchange rate returns within each month for the period of … the floating exchange rate. The results also confirm that there is more volatility in exchange rate when political …

discrete time models against high frequency estimates based on continuous time theory. In explanatory financial return …

examines how well exchange rate volatility explains movements in stock market returns. The model-based predictions are …

characterized by dramatic currency volatility. Burdens on the NYSE and home market to restore price parity for cross-listed stocks …

volatility (RV) of ten global stock market indices in the period from January 2000 to December 2021. We train models using a …

Two volatility forecasting evaluation measures are considered; the squared one-day ahead forecast error and its … standardized version. The mean squared forecast error is the widely accepted evaluation function for the realized volatility … standardized with its volatility. The statistical properties of the forecast errors point the standardized version as a more …