DC11: Applications of Agent-based Models (ABM) to analyse finance growth in a sustainable manner over a long-term period

Objectives

Agent-based systems are computer models that simulate the behaviours and interactions of autonomous agents, either as individuals or in groups, in order to gain a deeper understanding of how a system behaves and what factors influence its outcomes. In agentbased modelling, a system is represented as a collection of autonomous decision-making units, or agents (ABM). Each agent evaluates its own situation and makes decisions according to a set of rules. The literature contains few ABM studies that model economies and markets while assuming the industry's adoption of sustainable finance.

Expected Results

This study aims to use agent-based models to simulate different market scenarios in which industry agents take sustainable actions. Long-term financial growth will be analysed, and the findings will aid in the development and modification of industry policies and strategies. A public repository containing a library of the developed agent-based models is another anticipated outcome. The WP will place a strong emphasis on disseminating and the anticipated outcomes.

Secondments (2)

Recruitment & Hosting Details

DC 11 KUT Kaunas University of Technology M9 36

12

DC 11 KUT KUT Month 9 36 months D 5.3

Applications of Agent-based Models (ABM) to analyse finance growth in a sustainable manner over a long-term period (WP 5)

32

Project: 101119635 — DIGITAL — HORIZON-MSCA-DN-2022

Objectives: Agent-based systems are computer models that simulate the behaviours and interactions of autonomous agents, either as

individuals or in groups, in order to gain a deeper understanding of how a system behaves and what factors influence its outcomes. In

agentbased modelling, a system is represented as a collection of autonomous decision-making units, or agents (ABM). Each agent evaluates

its own situation and makes decisions according to a set of rules. Agents are capable of a variety of appropriate behaviours for the system

they represent. ABM has been utilised in numerous financial investigations. The literature contains few ABM studies that model economies

and markets while assuming the industry's adoption of sustainable finance.

Expected Results: This study aims to use agent-based models to simulate different market scenarios in which industry agents take

sustainable actions. Long-term financial growth will be analysed, and the findings will aid in the development and modification of industry

policies and strategies. A public repository containing a library of the developed agent-based models is another anticipated outcome. The

WP will place a strong emphasis on disseminating and the anticipated outcomes. Several channels, including peer-reviewed articles in

highimpact journals, research talks at national and international conferences, and use case presentations at industry workshops, will be

utilised to accomplish this objective.

Planned secondments:Royalton, Dr. Michael Althof, M21, 18 months, research on crypto assets for prototype and user acceptance ARC,

Prof. Dr. Ioannis Emiris, M39, 6 months, applied industry-research, using large-scale computing infrastructure to implement the theory

Fellow Host institution PhD enrolment Start date Duration Deliverables

12

Deliverables