Federal Funds Rate Prediction

35 Pages Posted: 21 Oct 2004

See all articles by Lucio Sarno

Lucio Sarno

City University London - Sir John Cass Business School; Centre for Economic Policy Research (CEPR)

Daniel L. Thornton

Federal Reserve Bank of St. Louis - Research Division

Giorgio Valente

Hong Kong Monetary Authority - Hong Kong Institute for Monetary Research (HKIMR)

Date Written: September 2004

Abstract

We examine the forecasting performance of a range of time-series models of the daily US effective federal funds (FF) rate recently proposed in the literature. We find that: (i) most of the models and predictor variables considered produce satisfactory one-day-ahead forecasts of the FF rate; (ii) the best forecasting model is a simple univariate model where the future FF rate is forecast using the current difference between the FF rate and its target; (iii) combining the forecasts from various models generally yields modest improvements on the best performing model. These results have a natural interpretation and clear policy implications.

Keywords: Federal fund rate, forecasting, term structure, nonlinearity

JEL Classification: E47, E43

Suggested Citation

Sarno, Lucio and Thornton, Daniel L. and Valente, Giorgio, Federal Funds Rate Prediction (September 2004). CEPR Discussion Paper No. 4587. Available at SSRN: https://ssrn.com/abstract=608245

Lucio Sarno (Contact Author)

City University London - Sir John Cass Business School ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

Centre for Economic Policy Research (CEPR)

London
United Kingdom

Daniel L. Thornton

Federal Reserve Bank of St. Louis - Research Division ( email )

411 Locust St
Saint Louis, MO 63011
United States
314-444-8582 (Phone)
314-444-8731 (Fax)

HOME PAGE: http://research.stlouisfed.org/econ/thornton/

Giorgio Valente

Hong Kong Monetary Authority - Hong Kong Institute for Monetary Research (HKIMR) ( email )

3 Garden Road, 8th Floor
Hong Kong
China

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