I am trying to build up a factor model for gold. To be able to identify the correct factors, I did a correlation analysis between a few factors vs gold and I integrated this analysis with what I saw in literature. I ended up with a set of factors as: VIX Index, EURUSD currency, H15X10YR Index (which is the US 10YR real rate). However, after running my ridge regression (I choose ridge due to the fact that I had already an idea of the factors and they are only 3, otherwise in case of many factor and no idea I would opt for lasso), my adjusted R2 is "only" 36%..am I missing something? after checking the time history I see that the gold has quite a similar trend with my factors, especially with the H15X10YR Index, but my level of "explicability" is only 36%. Can anybody highlight me on the reason of this please? Luigi
I will assume you are using factors and gold returns that are contemporaneous. With that setup, you are essentially trying to explain or decompose gold returns.
For an explanatory regression of a commodity (which is internationally traded), an $R^2$ of 36% is pretty good. Lots of factors can affect gold returns: Indian wedding season (a major effect on gold markets which you should not overlook), volatility in developing market currencies, and hyperinflation in large economies. You are omitting all of those effects. To still explain 36% of the variance is something to be proud of.
You may have expected more, but working with returns reveals how explaining changes in an asset isn't as simple as just showing a few similar-looking plots and exclaiming voila! I would not be upset at getting a 36% $R^2$ for my first model and one using only three factors.