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

If you have reason to think that yesterday's forecast went wrong, there is no glory in sticking to it.

People don't have a good intuitive sense of how to weigh new information in light of what they already know. They tend to overrate it.

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.

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.