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Big data can't save you, nor clever models

Investors are far too impressed with data and models and are not listening to experience and common sense

Big data can't save you, nor clever models

There's a video of the ecologist Allan Savory on YouTube, an extract from the documentary 'Return to Eden,' where he talks about the difference between science and academia.

What is science? People talk glibly about science, what is science? People coming out of a university with a Master's degree or a PhD, you take them into the field and they literally don't believe anything unless it's a peer-reviewed paper. It's the only thing they accept and if you say to them that let's observe, let's think, let's discuss, they don't do it...I think it's pathetic, going into universities as bright young people, they come out of them brain dead not even knowing what science means, they think it means peer-reviewed papers, etc. No, that's academia and if a paper is peer-reviewed it means everybody thought the same therefore they approved it...!

Of course, this is not really just about science. Savory's lament fits almost any field where there's a theoretical aspect and there's a practical world where a large number of practitioners have to make their way through the real world. Investments are a prime example, and one I'm most familiar with. There's far too much emphasis on impressing customers with theoretical models and back-testing and stress tests and the like and not enough on common sense and experience.

One common theme that runs through all the theoretical gyan is the idea (sometimes implicit but often explicit) that the more data you have and the more closely you study the past, the better you will understand the future. More data equals better decisions is pretty much a religion at this point.

However, here's a great counterpoint from Nassim Nicholas Taleb, the ex-trader and writer of 'The Black Swan' and many other books that everyone should read. Here, Taleb is answering an interview question on what people should learn if they want to understand investing. "I would tell people to learn more accounting, more computer science, more business history, more financial history. And I would ban portfolio theory immediately. It's what caused the problems. Frankly, anything in finance that has equations is suspicious. I would also ban the use of statistics because unless you know statistics very, very well, it's a dangerous, double-edged sword...The field of statistics is based on something called the law of large numbers: as you increase your sample size, no single observation is going to hurt you. Sometimes that works. But the rules are based on classes of distribution that don't always hold in our world...It uses metrics like variance to describe risk, while most real risk comes from a single observation, so variance is a volatility that doesn't really describe the risk."

Please read that quote again, carefully. Any investor should take every sentence of that statement as gospel. The phrase 'most risk comes from a single observation' sums up pretty much every bad thing that I have seen happen to investment portfolios over some decades. The distribution of risk in investments is highly skewed and numerical methods of quantifying it are adequate only in providing an analysis of the past. Most of the time, it can also provide an indication to the future. Unfortunately, once in a while, 'most of the time' is not enough.

All you need to do is to look back at the two great shocks of the last 20 years - the financial crisis of 2007-08 and now Covid, to appreciate how, for almost every investor, most risk will come from a single event. By definition, this single event will not be predictable, whether you are using big data, medium data or just small data. It's not about data at all.

Instead of trying to understand the investment world theoretically, it's better to gather some experience and make sure that when the big risky thing happens, you emerge on your feet.

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