Abstract

A popular class of yield curve models is based on the Nelson and Siegel approach of ‘fitting’ yield curve data with simple functions of maturity. However, such models cannot be consistent across time. This article addresses that deficiency by deriving an intertemporally consistent and arbitrage‐free version of the Nelson and Siegel model. Adding this theoretical consistency expands the potential applications of the Nelson and Siegel approach to exercises involving a time‐series context, such as forecasting the yield curve and pricing interest rate derivatives. As a practical example, the intertemporal consistency of the model is exploited to derive a theoretical framework for forecasting the yield curve. The empirical application of that framework to United States data results in out‐of‐sample forecasts that outperform the random walk over the sample period of almost 50 years, for forecast horizons ranging from six months to three years.

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