The recovery of real-estate market post-Covid
Start Date
August 2025
End Date
August 2025
Location
ALT 306
Abstract
The COVID-19 pandemic caused unprecedented disruptions to the real estate market, with significant fluctuations in housing prices, population shift, transaction volumes, and supply-demand dynamics. This study explores the post-pandemic recovery of the real estate market in Hamilton County, Ohio, through preliminary analysis and data visualization. Using data from 2018 to 2025, we examine trends in key market indicators such as housing prices, inventory levels, mortgage rates, and unemployment. Through graphical analysis, we uncover patterns, correlations, and potential drivers of market fluctuations. While the current focus is on understanding these relationships visually, this work lays the foundation for future development of mathematical models — including deterministic and stochastic differential equations — to describe and forecast the recovery process more rigorously. The study offers early insights into the structure and volatility of the housing market, with potential implications for policymakers, investors, and urban planners interested in long-term market resilience.
The recovery of real-estate market post-Covid
ALT 306
The COVID-19 pandemic caused unprecedented disruptions to the real estate market, with significant fluctuations in housing prices, population shift, transaction volumes, and supply-demand dynamics. This study explores the post-pandemic recovery of the real estate market in Hamilton County, Ohio, through preliminary analysis and data visualization. Using data from 2018 to 2025, we examine trends in key market indicators such as housing prices, inventory levels, mortgage rates, and unemployment. Through graphical analysis, we uncover patterns, correlations, and potential drivers of market fluctuations. While the current focus is on understanding these relationships visually, this work lays the foundation for future development of mathematical models — including deterministic and stochastic differential equations — to describe and forecast the recovery process more rigorously. The study offers early insights into the structure and volatility of the housing market, with potential implications for policymakers, investors, and urban planners interested in long-term market resilience.
