I have created a simple composite factor consisting of the ROIC, debt/equity, and FCF yield (each ranked then equal-weighted). Using Alphalens, the IC is about 0.02 on a 1-2 week time horizon. Based on some of the Quantopian videos I have seen, this is a "decent" IC. The quantile plot looks alright as well; there seems to be a monotonic relationship. I have a couple of questions:
Firstly, how does this reconcile with the sector quantile plots, which look pretty bad? Is it just the case that although the sector quantile plots don't seem to show any discriminatory power, the signal is predictive in aggregate?
Related to the above, is it generally the case that signals with ICs of more than 0.01 (or whatever number you consider "good") also have "good" (i.e monotonic) quantile plots?
Lastly, and this may be much more subjective: what do you normally have to see in an Alphalens tear sheet to encourage you to move into the IDE and start building a backtest? Is it a simple "if IC > 0.01 and quantile plot looks good" decision? In the interests of both time and avoiding overfitting, I don't want to be too trigger-happy with the backtesting.
I have a couple of factors which produce ICs of 0.01-0.03 in the research environment and wonder how I should be proceeding.