Risk as Challenge: A Dual System Stochastic Model for Binary Choice Behavior

TL;DR

This paper introduces Challenge Theory, a psychological model for binary risk decision-making that predicts choice popularity effectively, challenging traditional economic models and emphasizing cognitive factors.

Contribution

It presents a new CT-based regression model that predicts binary risk choices using a single Challenge Index, aligning with Prospect Theory effects.

Findings

High correlation between Challenge Index and choice popularity (r=-0.92, r=-0.93)

Model performs well on empirical data from 126 respondents and 44 choice problems

Simplifies psychological effects into a single index, enhancing predictive power

Abstract

Challenge Theory (CT), a new approach to decision under risk departs significantly from expected utility, and is based on firmly psychological, rather than economic, assumptions. The paper demonstrates that a purely cognitive-psychological paradigm for decision under risk can yield excellent predictions, comparable to those attained by more complex economic or psychological models that remain attached to conventional economic constructs and assumptions. The study presents a new model for predicting the popularity of choices made in binary risk problems. A CT-based regression model is tested on data gathered from 126 respondents who indicated their preferences with respect to 44 choice problems. Results support CT's central hypothesis, strongly associating between the Challenge Index (CI) attributable to every binary risk problem, and the observed popularity of the bold prospect in that problem (with r=-0.92 and r=-0.93 for gains and for losses, respectively). The novelty of the CT perspective as a new paradigm is illuminated by its simple, single-index (CI) representation of psychological effects proposed by Prospect Theory for describing choice behavior (certainty effect, reflection effect, overweighting small probabilities and loss aversion).