In Investing The Counter To Fooled By Randomness Is Fooled By Narrative

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During his recent interview with Tobias, Corey Hoffsten provides some great insights into how investors can be fooling themselves by coming up with a narrative and then data-mining the facts to fit that narrative, saying:

Corey: Yeah, I think it sounds wonderful and flowery and intuitive to say, “Hey, I want the economic rationale, why would I invest in something without the economic rationale?” But I think the counter to fooled by randomness is fooled by narrative, right?

If I discover an anomaly and then come up with a rationale as to why that anomaly works, am I just fooling myself into believing that narrative? If I come up with narrative and then data-mine the facts to fit that narrative, am I any better off necessarily?

So I think it is one of these things, as a quant we always try to say, “Hey we’re evidence-based.” The real truth is, the amount of evidence we have at our hands is very, very limited. Financial markets, there’s really just a few driving forces, we’ve only seen a few big regime shifts over the last 50 years, and arguably some of those regime shifts make prior data totally worthless.

I mean, is anything prior to World War Two really relevant? The advancements we’ve seen in technology and access to information and our education about financial markets really raises the question of, is some data and some anomaly that works back in 1910, is that relevant?

We tell ourselves, yes and we’re looking for this robustness across countries and geographies and asset classes and history, and I do think that is a good start, but I think it’s always good to keep in the back of our mind, everyone’s looking at the same data, everyone’s looking at the same anomalies, yeah that does help with the robustness conclusion, and hopefully there is some economic or behavioral risk-based intuition to whatever we’re trying to harvest. But at the end of the day, it is a limited data set that we keep going back to and trying to mine, and we do run the risk of at a certain point, just data-mining it to death.

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