Abstract

http://ssrn.com/abstract=384481
 


 



Measuring Variability and Stationarity of Term Premia for Interest Rate Forecasting


Ramon P. DeGennaro


University of Tennessee, Knoxville - Department of Finance

James T. Moser


American University - Kogod School of Business


Advances in Quantitative Analysis of Finance and Accounting, Vol. 3A, 1995

Abstract:     
We study a series of weekly term premia extracted from U.S. Treasury bill quotations from 1970-1982. We choose this period because it is characterized by high and variable inflation. We find that spot and forward rates are cointegrated and that the series of their differences is stationary. This implies that term premia are also stationary, which has implications for researchers seeking to improve interest rate forecasting. It also rules out several variables as determinants of term premia. We use a variance estimator that is consistent against autoregression to compute variance bounds. This lets us use overlapping observations, thus conserving degrees of freedom and letting us use a finer sampling interval. This estimator shows that both forecast errors and term premia are more variable than reported previously. Those earlier results used periods of low inflation, though, so our results are not necessarily inconsistent with them. Variation in the premium rises with the level.

JEL Classification: E4, G1

Accepted Paper Series


Not Available For Download

Date posted: April 22, 2003  

Suggested Citation

DeGennaro, Ramon P. and Moser, James T., Measuring Variability and Stationarity of Term Premia for Interest Rate Forecasting. Advances in Quantitative Analysis of Finance and Accounting, Vol. 3A, 1995. Available at SSRN: http://ssrn.com/abstract=384481

Contact Information

Ramon P. DeGennaro (Contact Author)
University of Tennessee, Knoxville - Department of Finance ( email )
423 Stokely Management Center
Knoxville, TN 37996
United States
865-974-1726 (Phone)
865-974-1716 (Fax)
James T. Moser
American University - Kogod School of Business ( email )
4400 Massachusetts Avenue NW
Washington, DC 20816-8044
United States
Feedback to SSRN


Paper statistics
Abstract Views: 269

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo3 in 0.454 seconds