We have referred to uncertainty as the gap between what we know and what we need to know. Uncertainty is the information gap and curiosity is the desire to close the gap. Curiosity is the core to being a good analyst and data detective.
For investing, it can start with just asking the simple question, "Why did the market move?" The investor who is not curious will say that the market moved higher because there were more buyers than sellers. It may not be said this simply, but it can be variation of supply and demand. The curious person will look for a cause but not a correlation. Yes, there was a new event but does that event explain the market move? Curiosity will be more than just looking at a news report that happened at the approximate time of the price move.
It can also apply to data. Where is the data coming from? How is it created? How is revised? Does it have delays? Is the data from one country the same as another?
We must fight the "illusion of explanatory depth" which stops us from digging deeper. A single level of depth or explanation may not be enough.
Inflation came in lower than expected so that is the reason for the market rally. This may be a good explanation, but it is not clear it is the right one. It may be the right one, but can it explain the size of the move? '
Can there be a limit to our curiosity, especially if you are a systematic modeler? No. The quantitative framework provides a framework for looking at countable events and repeatable responses. It allows a manager to focus on what is not countable and may be out of the ordinary.
See
Risk and uncertainty - The problem of closing the knowability gap
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