Novel Modelling of the Operation of the Financial Intermediary System – Agent-based Macro Models

Abstract

The study describes three agent-based macro models-expanded with the banking sector-that may later, following adequate further development, serve as bases for regulatory decisions. By presenting and explaining these models, the author attempts to make the readers understand the nature, essence and framework of agent-based modelling, also highlighting the difficulties that arise during modelling.

Explaining herding and volatility in the cyclical price dynamics of urban housing markets using a large-scale agent-based model

“…Their strength lies in the micro-interactions between individual decision-making agents (Tesfatsion 2006) each with their own characteristics; for example, businesses, households, or consumers, as well as spatial characteristics that geographically localize these interactions (Barthelemy 2016;Crosato et al 2018). These interactions can, in turn, be affected by banks' policies (Teglio et al 2012;Dosi et al 2013;Banwo et al 2019) and macroeconomics conditions (Cardaci 2018;Guilmi 2017;Mérő 2019). These agent-to-agent interactions produce complex (Jensen 2010), nonlinear effects such as tipping-points (Brock and Durlauf 2001;Harré et al 2019), boom-bust cycles (Geanakoplos et al 2012), and chaos Hommes 1998, Xin andHuang 2017), as well as the equilibrium dynamics predicted by classical models.…”