Agent-Based Modeling of Housing Price Cycles and Volatility

Summary

This study uses a large-scale agent-based model to examine why urban housing markets experience rising prices followed by sharp corrections. It represents households as heterogeneous agents whose decisions remain economically rational while allowing trend-following behavior. The model is calibrated with demographic, economic, and financial data from Greater Sydney across three distinct periods since 2006.

The reported simulations reproduce the price dynamics in those periods, including a sharp rise in price variability before the 2017 market peak. The authors link that behavior to the interaction of household trend-following, described as rational herding, and borrowing propensity. The account suggests a mechanism through which leverage and imitation can amplify housing-market cycles. Its evidence is specific to the modeled region and periods, and the brief description does not provide model details or out-of-sample validation. The findings may inform broader thinking about asset-market volatility, but they do not establish that the same dynamics apply to traded securities.

Key ideas

• Heterogeneous household agents can model housing-market dynamics while retaining economically rational decision-making.
• Trend-following behavior is important for reproducing cyclical price increases and corrections in the model.
• The model uses demographic, economic, and financial data from Greater Sydney across three periods since 2006.
• The model reproduces rising price variability before the 2017 peak and associates it with trend-following and borrowing propensity.

Tags

# 2004.07571


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









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 agent-based model populated by a large number of heterogeneous households. The agents' behavior is compatible with economic rationality, with the trend-following behavior found to be essential in replicating market dynamics. 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 (rational herding) and their propensity to borrow.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.