Using 'maximum likelihood estimation' to estimate EGARCH model parameters
Posted: Tue Aug 01, 2017 9:54 am
Hi,
Can anyone give me some advice on how to use Eviews to do the 'Maximum Likelihood estimation' to estimate the EGARCH parameters?
Step 1: Based on the Fama-french three-factor model to get the error term, Eq(1)
Step 2: The error term, which is the idiosyncratic return is assumed to have a normal distribution: Eq(2)
Step 3: The conditional variance of this error term is modeled using EGARCH process, same equation in Eviews Eq(3)
Step 4: The parameters estimated for Eq(1), Eq(2) and Eq(3) is from the 'maximum likelihood estimation
I am so confused on how to use this method in Eviews. Could anyone please give me some advice?
Can anyone give me some advice on how to use Eviews to do the 'Maximum Likelihood estimation' to estimate the EGARCH parameters?
Step 1: Based on the Fama-french three-factor model to get the error term, Eq(1)
Step 2: The error term, which is the idiosyncratic return is assumed to have a normal distribution: Eq(2)
Step 3: The conditional variance of this error term is modeled using EGARCH process, same equation in Eviews Eq(3)
Step 4: The parameters estimated for Eq(1), Eq(2) and Eq(3) is from the 'maximum likelihood estimation
I am so confused on how to use this method in Eviews. Could anyone please give me some advice?