The class of generalized autoregressive conditional heteroscedastic (GARCH) models has proved particularly valuable in modelling time series with time varying volatility. These include financial data, ...

This paper develops an empirical likelihood approach for regular generalized autoregressive conditional heteroskedasticity (GARCH) models and GARCH models with unit roots. For regular GARCH models, it ...

With volatility so closely tied to investment risk and returns, it's no wonder that a statistical method that captured time-varying volatility was deemed worthy of a Nobel Prize. Since its creation, ...