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  • Ryan Reeves

Optimal Research

Is it possible that doing too much research can hurt our investment performance? Allow me to explain.

The great thing about investing in the public markets is that the transaction costs are virtually zero. In financial terms, the only cost is any applicable capital gains taxes. And in non-financial terms, it’s a little bit of time to make the trades and update your spreadsheet. Since transaction costs are so low, the reversibility of a decision is quite high. I think it was Jeff Bezos who popularized this framework but the idea is that when you can easily reverse a decision, you shouldn’t actually take too much time making it. However, if you can’t reverse a decision, it makes sense to be more sure of the decision. Pretty obvious, right? He calls reversible decisions, two-way doors, and non-reversible ones, one-way doors.

Buying a stock is a two-way door. It’s quite easy to reverse the decision and make a new one. It’s not like a private business transaction where you can’t easily find a buyer, should you decide you want to sell. So by the framework, we shouldn’t actually take that much time to make our decisions.

That’s not to say that we shouldn’t have a checklist and do the table-stakes research. If you’re not doing that, you might as well buy an index and call it a day. Clearly, I believe in the power of research. But my point is that there are diminishing returns to research. There was an amazing study done that found beyond a certain amount of information, people’s decision-making abilities didn’t improve but their confidence did. That’s actually quite dangerous. That means you’re actively becoming more biased but tricking yourself into thinking it’s constructive.

This is a tricky topic because good investors can balance conviction and humility extremely well. One second they may be very excited about a stock but when they get a new piece of evidence that contradicts their hypothesis, they might sell immediately. That ability to update your view of something is absolutely crucial. And if you do an unnecessary amount of research, you may actually set yourself up to not being able to change your mind.

It’s all about confirmation bias – which along with anchoring, is one of the most dangerous investing biases. That’s why I’ve tried to shift from thesis-based investing to hypothesis-based investing. This may be a matter of semantics but a thesis is something you believe and a hypothesis is something you’re testing. A thesis sets you up to gather evidence. Just like a high-school English essay, you have your thesis and then your job is to find evidence to support that thesis. That process is the exact opposite in science. A hypothesis and a thesis are the same thing – something you think is true. However, the processes are the exact opposite. In science, you try falsifying your hypothesis. If you can’t falsify it, it becomes a theory or something that is temporarily true. I say temporarily because a scientific mindset leaves room for the fact that you could be wrong. So you’re trying to prove a thesis right and trying to prove a hypothesis wrong. The latter allows you to circumvent confirmation bias because you’re actively looking for disconfirming evidence.

So when you find something that falsifies your hypothesis, that’s great because now you’re one step closer to the truth. But it’s quite easy to dismiss a disconfirming piece of evidence in the face of a well-developed thesis. So maybe that’s the key? It’s not that we need less research, it’s that we need a different mindset as it relates to research. The point isn’t to gather evidence to support our ideas, it’s to constantly seek the truth.

Let’s use a concrete example. Imagine we are very excited about VR with all the talk about the metaverse lately. So our thesis is that VR will be the next big thing. We start gathering all this evidence that supports our proposition. Soon, we really believe VR will be the next big thing. And when we see data points that contradict our belief, it’s easy to make excuses like “those publications/people don’t know what they’re talking about.”

But a hypothesis needs to be a falsifiable statement like: “VR will be an industry that grows over 30% every year over the next 10 years.” If we start getting data that VR only grew 15% for the first year, we better have an awfully good reason why we think it should accelerate. But already, the hypothesis would be falsified. And now we would need to dig into the reasons why we thought it would be 30% and what happened that changed the actual facts. This is how better decision making happens.

This is why I like to invest in sectors where I know the numbers are actually booming. Investing by hope is much more risky. Going back to science, a scientific law is something that can be mathematically proven. Otherwise it’s not a law, it’s a theory. If we can blend our investment hypotheses into cold-hard numbers, it allows us to change our minds much more easily.


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