January 2010

Term Structure Forecasting Using Macro Factors And Forecast Combination

Michiel De Pooter, Francesco Ravazzolo, and Dick van Dijk

Abstract:

We examine the importance of incorporating macroeconomic information and, in particular, accounting for model uncertainty when forecasting the term structure of U.S. interest rates. We start off by analyzing and comparing the forecast performance of several individual term structure models. Our results confirm and extend results found in previous literature that adding macroeconomic information, through factors extracted from a large number of individual series, tends to improve interest rate forecasts. We then show, however, that the predictive power of individual models varies over time significantly. Models with macro factors are the more accurate in and around recession periods. Models without macro factors do particularly well in low-volatility subperiods such as the late 1990s. We demonstrate that this problem of model uncertainty can be mitigated by combining individual model forecasts. Combining forecasts leads to encouraging gains in predictability, especially for longer-dated maturities, and importantly, these gains are consistent over time.

Full paper (screen reader version)

Keywords: Term structure of interest rates, Nelson-Siegel model, affine term structure model, macro factors, forecast combination, model confidence set

PDF: Full Paper

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Last Update: September 18, 2020