gains over the equation by equation approach using a four variable fully interdependent model with different volatility …

estimator for forecasting time series, with a special attention to GARCH and ACD models. The local large sample properties of … suboptimal for forecasting purposes. The paper proposes the use of a class of shrinkage estimators that includes the Ridge …-daily financial durations forecasting application. The empirical application shows that an appropriate shrinkage forecasting …

This paper assesses the performance of volatility forecasting using focused selection and combination strategies to … include relevant explanatory variables in the forecasting model. The focused selection/combination strategies consist of … BIC. The methodology is applied to a daily recursive 1--step ahead value--at--risk (VaR) forecasting exercise of 4 widely …

Many ways exist to measure and model financial asset volatility. In principle, as the frequency of the data increases …, the quality of forecasts should improve. Yet, there is no consensus about a "true" or "best" measure of volatility. In … this paper we propose to jointly consider absolute daily returns, daily high-low range and daily realized volatility to …

In this paper we address the issue of forecasting Value–at–Risk (VaR) using different volatility measures: realized … baseline GARCH but not so relative to the range; there are relevant gains from modeling volatility trends and using realized … volatility, bipower realized volatility, two scales realized volatility, realized kernel as well as the daily range. We propose a …

predictors of interest), selective search within the range of possible models, control of collinearity, out-of-sample forecasting …