# ARMA estimates changed after GARCH [duplicate]

I have selected the best ARIMA(p,d,q) model via maximisation of AIC and got the estimates of its AR & MA coefficients.

However, after having subsequently modelled the conditional volatility with a GARCH(1,1) via rugarch package in $R$ (and having previously specified to consider ARMA(5,5) for conditional mean) the estimates for conditional mean comes out to be different!

Questions:

• Is it normal? Why just adding a model for conditional variance I'm affecting the conditional mean model?
• Should I force rugarch to use the the same estimates I got before by modelling just the residuals of the ARMA(5,5) model with GARCH? Would I get "better estimates" or not?
• In addition to the answer linked above, here is an intuitive argument. GARCH implies the observations have different conditional variances at different time points. Answer to Q1: Efficient estimation of a conditional mean model requires weighting the observations inversely proportionally to the conditional standard deviation. Answer to Q2: You should not force stepwise estimation as it is inefficient and moreover can be inconsistent. – Richard Hardy Apr 29 '18 at 12:15