This paper sets up a statistical framework for modeling realized volatility (RV) using Dynamic Conditional Score (DCS) model. It first shows how, dataset on stock indices, preliminary analysis of RV, based fitting linear Gaussian model to its logarithm, suggests the use two component dynamic specification. also indicates departure from normality, weekly pattern in data and presence heteroscedas...

We forecast the realized and median volatility of agricultural commodities using variants heterogeneous autoregressive (HAR) model. obtain tick-by-tick data on five widely-traded (corn, rough rice, soybeans, sugar, wheat) from CME/ICE. Real out-of-sample forecasts are produced for between 1 66 days ahead. Our in-sample analysis shows that HAR model which decompose measures into their continuous...

We use an international dataset on 5-min interval intraday data covering nine leading markets and regions to construct measures of realized volatility, jumps, skewness, kurtosis returns Real Estate Investment Trusts (REITs) over the daily period September 2008 August 2020. study out-of-sample predictive value skewness for volatility above where we also differentiate between “good” “bad” volatil...