Forecasting U.S. home foreclosures with an index of internet keyword searches

Abstract

Finding data to feed into financial and risk management models can be challenging. Many analysts attribute a lack of data or quality information as a contributing factor to the worldwide financial crises that seems to have begun in the U.S. subprime mortgage market. In this paper, a new source of data, key word search statistics recently available from Google, are applied in a experiment to develop a short-term forecasting model for the number of foreclosures in the U.S. housing market. The keyword search data significantly improves forecast of foreclosures, suggesting that this data can be useful for financial risk management. More generally, the new data source shows promise for a variety of financial and market analyses. © 2009 Springer Berlin Heidelberg.