The objective of this proposal is to create a tool able to predict housing price bubbles by analyzing the long-term behavior of housing prices using sequential forecasting ML algorithms. Unlike common practices that deal with macroeconomic variables, we suggest focusing on dynamic micro-factors, such as neighborhood’s architectural characteristics, urban planning and changing socio-economic factors.
