To the extent that you can find ways where you're making predictions, there's no substitute for testing yourself on real-world situations that you don't know the answer to in advance.

The thing that people associate with expertise, authoritativeness, kind of with a capital 'A,' don't correlate very well with who's actually good at making predictions.

The key to making a good forecast is not in limiting yourself to quantitative information.

We want to get 80%-85% of predictions right, not 100%. Or else we calibrated our estimates in the wrong way.

Whenever you have dynamic interactions between 300 million people and the American economy acting in really complex ways, that introduces a degree of almost chaos theory to the system, in a literal sense.

You can build a statistical model and that's all well and good, but if you're dealing with a new type of financial instrument, for example, or a new type of situation - then the choices you're making are pretty arbitrary in a lot of respects.