We evaluate the statistical and economic differences between affine term-structure models. Despite the voluminous literature on this subject, we have a limited understanding of those structural features of the models that are important in practice. Given that the key distinguishing characteristic of the affine models is the specification of the conditional volatility of the factors, we explore models that have critical differences in this respect: Gaussian (constant volatility) and stochastic volatility models. We estimate the models using the Eurodollar futures and options data as a basis. We subject these models to an exhaustive set of diagnostics. In particular, we develop a finite-sample version of the encompassing test for non-nested models. We find, based on the statistical tests and pricing errors, that there is little difference between the models when the models are estimated using only the yield curve information. Using options data enables us to separate the models very clearly. The stochastic volatility model is the most successful according to our diagnostics
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