Yield Curve and Recession Forecasting in a Machine learning framework.pdf
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Comput Econ (2015) 45:635–645
DOI 10.1007/s10614-014-9432-0
Yield Curve and Recession Forecasting in a Machine
Learning Framework
Periklis Gogas · Theophilos Papadimitriou ·
Maria Matthaiou · Efthymia Chrysanthidou
Accepted: 10 March 2014 / Published online: 27 March 2014
© Springer Science+Business Media New York 2014
Abstract In this paper, we investigate the forecasting ability of the yield curve in terms
of the U.S. real GDP cycle. More specifically, within a Machine Learning framework,
we use data from a variety of short (treasury bills) and long term interest rates (bonds)
for the period from 1976:Q3 to 2011:Q4 in conjunction with the real GDP for the same
period, to create a model that can successfully forecast output fluctuations (inflation
and output gaps) around its long-run trend. We focus our attention in correctly fore-
casting the instances of output gaps referred for the purposes of our analysis here as
recessions. In this effort, we applied a Support Vect
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