  In seeking to explain aspects of real-world economies that defy easy
understanding when analysed via conventional means, Nobel Laureate Robert
Shiller has since 2017 introduced and developed the idea of Narrative
Economics, where observable economic factors such as the dynamics of prices in
asset markets are explained largely as a consequence of the narratives (i.e.,
the stories) heard, told, and believed by participants in those markets.
Shiller argues that otherwise irrational and difficult-to-explain behaviors,
such as investors participating in highly volatile cryptocurrency markets, are
best explained and understood in narrative terms: people invest because they
believe, because they have a heartfelt opinions, about the future prospects of
the asset, and they tell to themselves and others stories (narratives) about
those beliefs and opinions. In this paper we describe what is, to the best of
our knowledge, the first ever agent-based modelling platform that allows for
the study of issues in narrative economics. We have created this by integrating
and synthesizing research in two previously separate fields: opinion dynamics
(OD), and agent-based computational economics (ACE) in the form of
minimally-intelligent trader-agents operating in accurately modelled financial
markets. We show here for the first time how long-established models in OD and
in ACE can be brought together to enable the experimental study of issues in
narrative economics, and we present initial results from our system. The
program-code for our simulation platform has been released as freely-available
open-source software on GitHub, to enable other researchers to replicate and
extend our work
