The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper compares Generalized Autoregressive Score (GAS) models and GARCH‐type models on their forecasting abilities for crude oil and natural gas spot and futures returns from developing and developed markets over multiple horizons. The out‐of‐sample forecasting results based on two loss functions and the Diebold–Mariano predictive accuracy test for multiple models show that the GAS framework outperforms...
This paper applies generalized autoregressive score‐driven (GAS) models to futures hedging of crude oil and natural gas. For both commodities, the GAS framework captures the marginal distributions of spot and futures returns and corresponding dynamic copula correlations. We compare within‐sample and out‐of‐sample hedging effectiveness of GAS models against constant ordinary least square (OLS) strategy...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.