Everyone today was wondering why the stock market was up so big even though the election was too close to call. Doesn’t the market dislike uncertainty?
Well I have answers for you.
(You should already distrust this statement)
I am going to tell you why the market was up today with a completely plausible rationale. You will feel the urge to accept my explanation because it will be believable (resist the urge), and also because it is almost your bedtime.
Ok, here goes:
The market is pricing in the possibility of a Biden win and a Republican controlled Senate. A divided government makes it less likely Biden would be able to push through stiffer regulations and higher taxes. Additionally, a new stimulus bill will likely get approved regardless of who is president. The market likes that stimulus can now be the main focus.
How’d I do? Believable?
Here’s why that explanation is largely noise:
The explanation above is an example of mechanical thinking: trying to boil everything down to atomic pieces of cause and effect blocks that explain in logical order how one thing explains another.
As humans, we capital L Love mechanical thinking because it fits a narrative structure very well, and we are very good at deriving actionable insights from narratives. It’s kind of a superpower of ours.
But if you think just a bit longer about it, mechanical thinking is very good at explaining and not very good at predicting. If the market was down today, I could have given a slightly adjusted yet equally plausible explanation.
What’s actually going on is probably better considered using Systems Thinking. While mechanical thinking seeks to explain by zooming into cause and effects, Systems Thinking zooms out and tries to think of the problem space as being one part of a much more complex, larger system.
The larger system has a lot more going on: feedback loops, interconnectedness, synthesis, and emergence. To shorthand it: it’s more complex than a 6-year PhD thesis dissertation.
We’re not going full butterfly-effect you-can’t-predict-anything here, only making the point that the behavior of a system depends on its entire environment and not just adding up the behavior of its different pieces.
The point I want to leave you with is that mechanical thinking won’t help you generate alpha before the event occurs (you know, when you have to act in order to take advantage of it), and systems thinking is so complex, it’s better to approach it by learning a bit every day; and only over time realizing pattens and drawing inferences that you can act on.
Even a fast growing company can only grow so much in a single day. You are the same way. Try to learn something new every day, and think about markers moves in the broader context of the system it exists in.