# ARMA-GARCH model: evaluate which factors affect the return of an asset

I'm working with data that includes the returns on a financial asset and 10 other variables (for example Google-searches). My aim is to test which of these factors affect the return (not the volatility). ARMA+GARCH is the model I am supposed to use for this study.

My questions are as follows:

1. Will the model, which I run in R, test the impact of all the variables, or do I need to test them separately?
2. Also, is there anything I should take into account about my data? My returns are log returns, but I could use percent-returns instead.
3. Is it possible to test with different lags?

Incorporate the extra variables and/or their lags in your conditional mean equation next to the ARMA terms.

In R you can do that by using the package "rugarch" and functions ugarchspec and ugarchfit.

• Specify the model with ugarchspec by including these variables via the argument external.regressors within the argument mean.model.
• Estimate the model with ugarchfit.

The reported coefficients from the conditional mean equation will tell you the effect sizes of these variables.