Tuesday, June 22, 2010

Reducing uncertainty

In How to Measure Anything (Wiley, 2010) Douglas Hubbard confronts a common measurement myth—that when you have a lot of uncertainty, you need a lot of data to tell you something useful. The fact is that “if you have a lot of uncertainty now, you don’t need much data to reduce uncertainty significantly. When you have a lot of certainty already, then you need a lot of data to reduce uncertainty significantly.” (p. 110)

I think that traders and investors should take this to heart. In a world of great uncertainty we shouldn’t overanalyze a situation assuming that the results will be proportional to the effort. A single price bar or data point might be all that’s necessary to reduce uncertainty significantly. Waiting for the next three price bars or data points may in fact only increase uncertainty.

There’s a reason that good traders often act first and think later. Moreover, when they start thinking after they enter a trade, they’re not usually looking for more reasons to justify the trade or to make a favorable outcome more certain. (One exception might be if a trader is looking to scale into a position.) They’re thinking about all the things that could go wrong. Here again, they don’t need much to reduce their uncertainty about the viability of the trade. Any data that suggest the trade is ill advised should be taken seriously and not rationalized away. Act, then reassess.

Good traders can only try to reduce uncertainty, not attain certainty. It’s wise to do this in the most efficient and cost effective way possible.

1 comment:

  1. I so agree with: “if you have a lot of uncertainty now, you don’t need much data to reduce uncertainty significantly. When you have a lot of certainty already, then you need a lot of data to reduce uncertainty significantly.”

    By the way, I'm a huge fan of your blog. I'm envious of your ability to gobble up books so rapidly!

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