Center for Artificial Intelligence in Business Analytics and Financial Technology

COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK

Center for Artificial Intelligence in Business Analytics and Financial Technology

JPMorgan

project description

Determine drivers of home prices in Metropolitan areas (MSA’s) in order to identify MSA’s with the potential for the highest amount of dynamic growth over the next five- to ten-year period. Our approach to this project has been to use home prices as our target feature (Home Price Indices are provided by the Federal Housing Finance Agency for 383 Metropolitan Statistical Areas within the United States) and approximately 30 economic, demographic, and financial features to determine drivers and leading indicators of long-term home price movements in each metropolitan area.
Throughout this project, we have continually found that high-level data (GDP, population, inflation, interest rates, etc.) are insufficient for understanding the nuances of housing markets. As a result, our work has involved a tremendous amount of problem structuring to better recognize important market drivers and players at a tremendous level of detail, allowing for a much deeper appreciation of why markets move and how we can predict those moves with a high level of accuracy.
For a large real estate organization or bank like JPMorgan, knowing which markets are prime for growth and the behavior of some markets compared to other markets can prove extremely valuable for asset allocation decisions within their various portfolios.
Decomposition of the relationship between the Home Price Index (HPI) and the Consumer Price Index (CPI). Here we see that periods where home prices are increasing faster than the CPI for a prolonged period of time, a drop in home prices typically follows and seems to be related to both the magnitude of the difference between HPI and CPI and also the length of time that home price appreciation outpaces consumer inflation.
Decomposition of the relationship between the Home Price Index (HPI) and the Consumer Price Index (CPI). Here we see that periods where home prices are increasing faster than the CPI for a prolonged period of time, a drop in home prices typically follows and seems to be related to both the magnitude of the difference between HPI and CPI and also the length of time that home price appreciation outpaces consumer inflation.
When comparing the increase in housing prices to household income over time, we see that the income growth for the lower income brackets has fallen far behind the growth in home prices, making homes less and less affordable over time for these lower income households.
When comparing the increase in housing prices to household income over time, we see that the income growth for the lower income brackets has fallen far behind the growth in home prices, making homes less and less affordable over time for these lower income households.