A few weeks ago, Numerai added feature neutral correlation (FNC) to the leaderboard. I’m curious, do you use FNC as a measure of performance in your model development?
- Yes, it’s my primary measure of performance.
- Yes, it’s an important indicator.
- Yes, but I don’t think it’s an important indicator.
I’d be happy to hear your thoughts about FNC in the comments as well!
Disclosure: In my own backtesting, I have found FNC to be a worse predictor of future performance (measured by correlation) than sharpe and certainly than correlation. For me, it also didn’t add anything beyond correlation as a predictor of performance. And since we are also not paid for FNC, I don’t use it in my process at all. In my humble opinion, FNC has a weak theoretical basis and should not appear right next to CORR and MMC, the two measures that actually determine our payout.