Forecasting interest rate swap spreads using domestic and international risk factors: Evidence from linear and non-linear models

Costas Milas, Ilias Lekkos and Theodore Panagiotidis ()
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Ilias Lekkos: Research Department, Eurobank Ergasias, Greece

No KERP 2006/05, Keele Economics Research Papers from Centre for Economic Research, Keele University

Abstract: This paper explores the ability of factor models to predict the dynamics of US and UK interest rate swap spreads within a linear and a non-linear framework. We reject linearity for the US and UK swap spreads in favour of a regime-switching smooth transition vector autoregressive (STVAR) model, where the switching between regimes is controlled by the slope of the US term structure of interest rates. We compare the ability of the STVAR model to predict swap spreads with that of a non-linear nearest-neighbours model as well as that of linear AR and VAR models.We find some evidence that the non-linear models predict better than the linear ones. At short horizons, the nearest-neighbours (NN) model predicts better than the STVAR model US swap spreads in periods of increasing risk conditions and UK swap spreads in periods of decreasing risk conditions. At long horizons, the STVAR model increases its forecasting ability over the linear models, whereas the NN model does not outperform the rest of the models.

Keywords: Interest rate swap spreads; term structure of interest rates; factor models; regime switching; smooth transition models; nearest-neighbours; forecasting. (search for similar items in EconPapers)
JEL-codes: C51 C52 C53 E43 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-fmk, nep-for and nep-mac
Date: 2006-04
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Forthcoming in Journal of Forecasting

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Related works:
Working Paper: Forecasting interest rate swap spreads using domestic and international risk factors: Evidence from linear and non-linear models (2006)
Journal Article: Forecasting interest rate swap spreads using domestic and international risk factors: evidence from linear and non-linear models (2007)
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