Ergodicity transformations predict human decision-making under risk

Decision theories commonly assume that risk preferences can be expressed as utility functions, which vary from person to person but are stable over time. A recent model from ergodicity economics reveals that if people want their wealth to grow at the fastest rate they need to adjust their utility functions depending on the dynamics of their wealth. Here, we ask whether humans make such adjustments by exposing them to different wealth dynamics. We carried out an experiment in which participants made consequential risky decisions under two different conditions, additive and multiplicative wealth dynamics. We estimated risk aversion parameters separately in the two conditions for each participant, fitting isoelastic functions via hierarchical Bayesian models. In our pre-registered analyses, we found strong evidence for a change in utility function, namely an increase in the risk aversion parameter under the multiplicative condition, as predicted by ergodicity economics. Apart from evidence for a large effect of wealth dynamics, we also recover trait-like differences between participants that persist across the two conditions. Our study introduces a new experimental design and contains two independent replications between pilot data and a larger cohort. Together, these results provide evidence that human risk-taking behaviour is sensitive to the dynamical context in which decisions are made and that long-term wealth maximization is an important explanatory principle.