Prediction of variability in mortgage rates: interval computing solutions

Ling T. He, Chenyi Hu and K. Michael Casey

Journal of Risk Finance, 2009, vol. 10, issue 2, 142-154

Abstract: Purpose - The purpose of this paper is to forecast variability in mortgage rates by using interval measured data and interval computing method. Design/methodology/approach - Variability (interval) forecasts generated by the interval computing are compared with lower‐ and upper‐bound forecasts based on the ordinary least squares (OLS) rolling regressions. Findings - On average, 56 per cent of annual changes in mortgage rates may be predicted by OLS lower‐ and upper‐bound forecasts while the interval method improves forecasting accuracy to 72 per cent. Research limitations/implications - This paper uses the interval computing method to forecast variability in mortgage rates. Future studies may expand variability forecasting into more risk‐managing areas. Practical implications - Results of this study may be interesting to executive officers of banks, mortgage companies, and insurance companies, builders, investors, and other financial decision makers with an interest in mortgage rates. Originality/value - Although it is well‐known thatchanges in mortgage rates can significantly affect the housing market and economy, there is not much serious research that attempts to forecast variability in mortgage rates in the literature. This study is the first endeavor in variability forecasting for mortgage rates.

Keywords: Financial forecasting; Loans; Interest rates; United States of America (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (text/html)
https://www.emerald.com/insight/content/doi/10.110 ... d&utm_campaign=repec (application/pdf)
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eme:jrfpps:15265940910938224

DOI: 10.1108/15265940910938224

Access Statistics for this article

Journal of Risk Finance is currently edited by Nawazish Mirza

More articles in Journal of Risk Finance from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().