Investing, Fast & Slow. Part 1

My starting point is that, one way or another, investing is and will remain a fundamentally human activity.

To be more specific, investing is and will remain a cultural phenomenon that has evolved in a way which contributes to the growing role of intelligence in the universe. Fairly obviously, that evolution is itself evolving different tool sets to help do the job. Quantitative modelling has developed a whole sert of tactics, strategies and expressions which are new branches on the tree, but the tree remains fundamentally the same.

That the task has remained fundamentally the same is not obvious: as each new tool has arrived, intelligent people have feared that the game is changed. (Here's how Robert Mayo, then head of the Chicago Fed discussed with the FOMC the rise of the options market in the 1970s: 'My elbow is still uneasy about this. There is a counterculture, if you want to distinguish it that formally, developing now with the evolution of puts, that will counterbalance the calls, and the market will be better again. But this is getting into real mystique. I don’t think anyone really knows what he’s talking about.')

Even when computer-driven trading represents the majority of stockmarket activity, I'm prepared to take it as axiomatic that investment will remain a fundamentally human activity. That's partly because no matter how much data is fed into the algorithms, market pricing will retain its ability to discover information which can be discovered in no other way (Hayek's thesis). Indeed, if computer programs alone were able to remove unprogrammable surprise element from pricing, then there would be essentially no purpose to markets in the first place - we'd be better off simply allowing the computers, not markets, to allocate resources. We know how that ends, and it's not well (ironically, we might say the data is in on it.)

The ultimate impact of computer-driven trading in all its variety is mitigated by the enduring fact that at both the top and bottom of the investment-decision tree, humans get involved. At the bottom of the tree, we have humans making decisions about whether to invest and how to invest. Having made the decision to save, and save in equities, what governs the choice between single stocks, mutual funds, ETFs, family offices, hedge funds, or CDFs and derivatives of various kinds? Price, fashion, advice?

When an institutional vehicle is chosen, the way that institutional vehicle runs itself is constrained by irreducible human factors, including fashion, 'respectability', theoretical justification (portfolio theory etc). the regulatory environment, and the sensitivities of investors and trustees. And finally, at the top of the investment decision, the entire investment environment is affected by the decisions of the 12 people on the FOMC. History provides abundant evidence of human intelligence and fallibility in their decisions.

Essentially then, investing is a human activity, and therefore an expression of human thought.

Which brings us to Daniel Kahneman and Amos Tversky and the book 'Thinking, Fast and Slow'. My guess is that you'll have recognized the reference in this piece's title. Kahneman's book gave birth to the field of behavioural economics and in its wake there have been a large number of usually unsuccessful attempts to deploy the insights of behavioural economics (ie, loss aversion etc) into investment strategy.

But it may be more useful to consider what he has to say more widely. At the heart of 'Thinking, Fast & Slow' is the description of two types of thinking. System 1 thinking is fast thinking, what we do, very often unknowingly or instinctively, to make snap decisions about situations we encounter all the time. By contrast, System 2 thinking is slow and deliberative, demanding an expenditure of energy in conscious effort. (And System 2 thinking is expensive: as someone said, 'Most of the world's problems can be solved with five minutes thought. But thinking is hard, and five minutes is a long time.')

It strikes me that since investing is an essentially human activity, we should understand that the results will always represent a mixture between the results of System 1 thinking and System 2 thinking. The suggested corollary is that if you rely solely on System 1 thinking (ie, you are a day-trader) you will sooner or later get beaten out of the market by the results of System 2 thinking/investing. But it's probably no less true that if you rely only on System 2 thinking, investing only in line with your carefully worked-out strategic insights, you will spend a lot of time getting killed by the 'irrational' activities of System 1 day-traders (who might well turn out to be algos anyway).

In other words, if investing is a fundamentally human activity, you need to have an approach which acknowledges and incorporates both System 1 and System 2 investing. You need to think about Investing, Fast & Slow.

I’ll start doing that in Part 2.