I'm trying to model several financial time series and to get some forecast on them.
Considering the log-returns, I fitted an EGARCH(1,1) on the data and got the parameters, as known constraint-free because of the model: $$ \text{log}(\sigma^2_t)=\omega + \alpha_1 g(\eta_{t-i}) + \beta \text{log}(\sigma^2_{t-j}) $$ which considers exponentation for the parameters.

So I fit the model with ugarchfit function from rugarch package in R and then I use the ugarchforecast function to get the unconditional volatility of series. In the output I can notice many negative prediction!

Is that a problem of model-validity or does the ugarchforecast function return the conditional log-volatility so I have to exponentiate my output?


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.