Is rationality the key to better investment decisions? Or is it better judgement?

Note: This article is written by Bob Collie, but was posted by Liang Yin because of techinical difficulties at the time. In this post – my first in the role of “new guy” in the Thinking Ahead Group – I will share some initial thoughts on a topic that we’ll be spending a lot of time on this year: investment decision-making. My starting point is the specific perspective of the investment world as being a complex adaptive system. This perspective underlies much of the work that TAI has created over the years, including papers such as Stronger investment theory and System thinking and investment. In loose terms, this view can be thought of as abandoning the characterisation of economics in general (and investment markets in particular) as analagous to the study of physics, and instead characterising them as more akin to biology. There’s a good description of the technical foundation of that distinction in a paper by Andrew Lo and Mark Muller. That change of perspective makes real-world phenomena – bubbles; crashes; prolonged spells of abnormally low or high market volatility; and so on – seem much less odd. The natural world is a messier, less-well-behaved system than the machine-like world of physics equations. It’s a better point of reference for making sense of market behaviour. The change of reference point leads to a different view of decision-making. Gary Klein, a psychologist, has studied in depth how experts such as firefighters and military officers make decisions in the field, with a focus on the successes of expert intuition. He is perhaps best known for having co-written with Daniel Kahneman the paper Conditions for Intuitive Expertise: A Failure to Disagree, a paper that describes itself as “an effort to explore the differences between two approaches to intuition and expertise that are often viewed as conflicting”. On the surface, Kahneman and Klein seem to represent different sides of an argument about the value of intuition and expert judgement. Yet the paper found a great deal more common ground than either expected. Notably, there was agreement that intuition is derived from recognition and that intuitive judgements are more valid in environments in which relationships are stable and where there is sufficient feedback to allow skill and expert intuition to develop. The two sides of the argument turned out to be at least in part a simple difference of focus: one discipline was looking into how to harness the remarkable power of skilled judgement, the other focusing on those instances where reliance on intuition tends to lead to error. The impact of the environment on the effectiveness of different approaches to decision-making is also found in Klein’s earlier work. In this, he compares the rational choice model – classical deductive reasoning – with what he terms naturalistic (or recognition-primed) decision making. An example of the latter approach is the way in which expert chess players draw on their skill in judging patterns to find good moves without conscious exploration of every possibility. Klein has characterised the conditions which are more amenable to each of these two approaches as follows:
Conditions that favour naturalistic decision-making Conditions that favour the rational choice model
Greater time pressure More experience Dynamic conditions Ill-defined goals Need for justification Conflict resolution Optimisation Computational complexity
Based on: G. Klein (1998) Sources of Power. MIT Press. In his discussion of this distinction, Klein specifically highlights investment portfolio analysis as an example of a decision that is computationally complex. That implies a need for rational, rather than intuitive, decision-making. But markets are not merely complex[1] systems, they are complex adaptive systems; their adaptive nature leads to dynamic conditions – a factor that appears on the other side of the table above. And that points to a need for the application of expert judgement and intuition rather than pure deductive reasoning. The very nature of the investment world is pulling us in two directions at once. Which means that the question in the title of this post doesn’t have an obvious answer. (Except, perhaps, “both”.) And this perhaps helps to explain why investment decision-making – a theme that TAI will be exploring in depth this year – is a thorny and fascinating topic. The recognition that investment markets are complex adaptive systems is a starting point. But making sense of the financial challenges faced by individuals, institutional asset owners, and the investment industry is a messy business, a task that cries out for thorough, rational, clear thinking and yet which no model will ever fully capture.

[1] Technically, what is meant by “complexity” in the context of a complex system is not quite the same thing as the plain-English version of complexity to which Klein’s table refers. The distinction is not important for the purposes of this post.