Affective-Cognitive Prospect Theory: An Integrative

Psychological-Economic Model of Decision-Making Under

Uncertainty

Dmitry Yagudin1,*

1 Doctor of Psychology, CEO of the D.R. Yagudin International Neuro University, Chairman of the Board of the Unity NGO, Russia

Email: dr.yagudin@mail.ru

Received: January 03, 2026 Revised: March 01, 2026 Accepted: April 15, 2026 ⋆ Corresponding author

ABSTRACT

Standard models of decision-making under uncertainty, from expected utility theory to cumulative prospect theory,

treat risk preferences as fixed individual traits. Yet a substantial psychological literature shows that risk-relevant

preferences shift systematically with the decision-maker’s momentary internal state: affective arousal amplifies

loss aversion, while cognitive load and time pressure push judgment toward heuristic, more distorted probability

processing. This paper proposes Affective-Cognitive Prospect Theory (ACPT), a state-dependent extension of

cumulative prospect theory in which the loss-aversion coefficient is an increasing function of affective arousal and

the curvature of the probability-weighting function is a decreasing function of cognitive load, each grounded in an

established psychological literature.

Keywords: Decision-making under uncertainty Prospect theory Loss aversion Probability weighting Affect

Cognitive load Behavioral economics Risk premium

1. INTRODUCTION

Expected utility theory long served as the normative and

descriptive benchmark for choice under risk, but its descriptive

adequacy was challenged early by systematic violations

documented in controlled experiments. Allais showed that

decision-makers routinely violate the independence axiom

when a common outcome is added to or removed from two

prospects, preferring certainty in one comparison and the

higher-variance option in the structurally equivalent second

comparison [1]. Ellsberg showed a parallel violation for uncertainty

about probabilities themselves, documenting a systematic

preference for known over unknown probabilities that

expected utility theory cannot accommodate [2]. Kahneman

and Tversky’s prospect theory, and its rank-dependent successor,

cumulative prospect theory, were developed to capture

these and related anomalies through two central departures

from expected utility: a value function defined over gains

and losses relative to a reference point, exhibiting loss aversion

and diminishing sensitivity, and a nonlinear probabilityweighting

function that overweights small probabilities and

underweights moderate-to-large ones [3, 4]. Three decades

on, cumulative prospect theory remains the best-supported

descriptive account of risky choice in experimental settings

and has been steadily incorporated into mainstream economic

modelling [5].

Even so, standard prospect theory shares a feature with the

expected-utility framework it was built to replace it treats the

parameters governing risk preference as fixed traits of the

individual, estimated once and assumed stable across occasions.

This assumption sits uneasily beside a large body of

psychological evidence that risk-relevant judgment is statedependent

rather than trait-fixed. The risk-as-feelings hypoth-