Abstract: What — if anything — can psychology and decision science contribute to risk management in financial institutions? The turmoils of recent economic crises undermine the assumptions of classical economic models and threaten to dethrone Homo oeconomicus, who aims to make decisions by weighing and integrating all available information. But rather than proposing to replace the rational actor model with some notion of biased, fundamentally flawed and irrational agents, we advocate the alternative notion of Homo heuristicus, who uses simple, but ecologically rational strategies to make sound and robust decisions. Based on the conceptual distinction between risky and uncertain environments this paper presents theoretical and empirical evidence that boundedly rational agents prefer simple heuristics over more flexible models. We provide examples of successful heuristics, explain when and why heuristics work well, and illustrate these insights with a fast and frugal decision tree that helps to identify fragile banks. We conclude that all members of the financial community will benefit from simpler and more transparent products and regulations.
|(…) we make search in our memory for a forgotten idea, just as we rummage our house for a lost object. In both cases we visit what seems to us the probable neighborhood of that which we miss. We turn over the things under which, or within which, or alongside of which, it may possibly be;
and if it lies near them, it soon comes to view.
|William James (1890), The Principles of Psychology, p. 654|
[Copyright neth.de, 2007–2014]:
Steve Payne, Geoff Duggan, Hans Neth (2007).
Discretionary task interleaving: Heuristics for time allocation in cognitive foraging.
Journal article in JEP:G.
Abstract: When participants allocated time across 2 tasks (in which they generated as many words as possible from a fixed set of letters), they made frequent switches. This allowed them to allocate more time to the more productive task (i.e., the set of letters from which more words could be generated) even though times between the last word and the switch decision (“giving-up times”) were higher in the less productive task. These findings were reliable across 2 experiments using Scrabble tasks and 1 experiment using word-search puzzles. Switch decisions appeared relatively unaffected by the ease of the competing task or by explicit information about tasks’ potential gain. The authors propose that switch decisions reflected a dual orientation to the experimental tasks. First, there was a sensitivity to continuous rate of return — an information-foraging orientation that produced a tendency to switch in keeping with R. F. Green’s (1984) rule and a tendency to stay longer in more rewarding tasks. Second, there was a tendency to switch tasks after subgoal completion. A model combining these tendencies predicted all the reliable effects in the experimental data.