There are several approaches to dealing with heteroscedasticity. If the error variance at different times is known, weighted regression is a good method. If, as is ...
One of the key assumptions of the ordinary regression model is that the errors have the same variance throughout the sample. This is also called the homoscedasticity ...
Buffered Autoregressive Models With Conditional Heteroscedasticity: An Application to Exchange Rates
This article introduces a new model called the buffered autoregressive model with generalized autoregressive conditional heteroscedasticity (BAR-GARCH). The proposed model, as an extension of the BAR ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback