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

Abstract

Urban housing markets, along with markets of other assets, universally exhibit periods of strong price increases followed by sharp corrections. The mechanisms generating such non-linearities are not yet well understood. We develop an agentbased model populated by a large number of heterogeneous households. The agents' behavioral rules are consistent with the concept of bounded rationality. The model is calibrated using several large and distributed datasets of the Greater Sydney region (demographic, economic and financial) across three specific and diverse periods since 2006. The model is not only capable of explaining price dynamics during these periods, but also reproduces the novel behavior actually observed immediately prior to the market peak in 2017, namely a sharp increase in the variability of prices. This novel behavior is related to a combination of trend-following aptitude of the household agents (herding) and their collective propensity to borrow. Trend-following behavior is found to be essential in replicating market dynamics.

The impact of social influence in Australian real-estate: market forecasting with a spatial agent-based model

“…This work extends the work of Glavatskiy et al (2020), which we will refer to as the "Baseline" method. In this section, we describe basic features of the baseline model, which the present work carries over.…”

“…A recent ABM of the Australian housing market proposed by Glavatskiy et al (2020) explained the volatility of prices over three distinct historic periods, characterised by either steady trends or trend reversals and price corrections. This model highlighted the role of the agents' trend-following aptitude in accurately generating distinct price dynamics, as detailed in Section 3.…”

A Maximum Entropy Model of Bounded Rational Decision-Making with Prior Beliefs and Market Feedback

“…To exemplify the model, we use the Greater Sydney house price dataset provided by SIRCA-CoreLogic and utilised in [53,54]. This dataset is outlined in Appendix B.…”

Etmen-tabanlı modellemede belirme ve karmaşıklık: Güncel araştırmaların incelenmesi

“…The application areas of agent-based modeling are very diverse. For example, simulations related to the spread of diseases (Hoertel et al, 2020), migration (Hébert et al, 2018), consumer behavior (Caprioli et al, 2020), economics (Glavatskiy et al, 2021), healthcare (Esposito et al, 2020), social interactions and networks (Kaligotla et al 2018), activity-travel behavior (Cenani et al, 2013;Macal et al, 2018), user/pedestrian movements (Cenani, 2008;Vizari et al, 2020), building/city evacuations in emergency situations (Li et al, 2016), urban and transportation planning (Park et al, 2018), traffic congestions (Vo et al, 2016), terrorist attacks (Lu et al, 2020), natural disasters such as tsunami, flood, earthquake (Costa et al, 2021;Haer et al, 2020;Wang and Jia, 2021) are among the research areas where agent-based models are frequently used. Meyers (2012) defines complex systems as "systems that comprise many interacting parts with the ability to generate a new quality of collective behavior through self-organization, e. g. the spontaneous formation of temporal, spatial or functional structures.…”