The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of … on the basis of their one-step ahead forecasting performance. With regard to forecast unbiasedness and precision …

The GARCH(1,1) model and its extensions have become a standard econometric tool for modeling volatility dynamics of … on the basis of their one-step ahead forecasting performance. With regard to forecast unbiasedness and precision …

Several procedures to forecast daily risk measures in cryptocurrency markets have been recently implemented in the … models, we evaluate the use of several forecast combining strategies. Our results, based on a comprehensive backtesting …

commonly used to forecast realized volatility, this paper also contributes to the literature by coupling realized measures with …In the past decade, the popularity of realized measures and various linear models for volatility forecasting has … the ongoing debate with a comprehensive evaluation of multiple-step-ahead volatility forecasts of energy markets using …

The aim of this paper is to investigate the relevance of structural breaks for forecasting the volatility of daily … returns on BRICS countries (Brazil, Russia, India, China and South Africa). The data set used in the analysis is the Morgan … order moment of the process and persistence in the variance, has been implemented. Some forecast combinations that account …

This paper considers forecast averaging when the same model is used but estimation is carried out over different … estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or … estimation windows leads to a lower bias and to a lower root mean square forecast error for all but the smallest of breaks …

This paper shows that combinations of option implied and time series volatility forecasts that are conditional on … used in this paper extends the application of conditional predictive ability tests to select forecast combinations. We show … that this method works well in practice by applying it to volatility forecasts for the Mexican Peso-US Dollar exchange rate …

An accurate weather forecast is the basis for the valuation of weather derivatives, securities that partially … precision of two forecast models of average daily temperature, the Ornstein-Uhlenbeck process (O-U process) and the generalized … 2018 forecast. Forecasted values were compared to the available actual data for 2018 using MAPE and RMSE methods. The GARCH …

This paper considers forecast averaging when the same model is used but estimation is carried out over different … estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or … estimation windows leads to a lower bias and to a lower root mean square forecast error for all but the smallest of breaks …

We investigate the question of whether macroeconomic variables contain information about future stock volatility beyond … that contained in past volatility. We show that forecasts of GDP growth from the Federal Reserve's Survey of Professional … Forecasters predict volatility in a cross-section of 49 industry portfolios. The expectation of higher growth rates is associated …