Knowledge that Transforms

We compare and contrast some existing ordinary least squares (OLS)- and generalized method of moments (GMM)-based tests of asset pricing models with a new more general test. This new test is valid under the assumption that returns are elliptically distributed, a necessary and sufficient assumption of the linear capital asset pricing model (CAPM). This new test fails to reject the CAPM on a dataset of stocks sorted by market valuations, whereas similar tests constructed from OLS and GMM estimation methods reject the linear CAPM. We also find that outliers reduce the OLS-estimated mispricing of the linear CAPM on monthly returns sorted by previous performance, that is, momentum. Monte Carlo evidence supports superior size and power properties of the new test relative to OLS- and GMM-based tests.

This article is a critical survey of models designed for pricing fixed-income securities and their associated term structures of market yields. Our primary focus is on the interplay between the theoretical specification of dynamic term structure models and their empirical fit to historical changes in the shapes of yield curves. We begin by overviewing the dynamic term structure models that have been fit to treasury or swap yield curves and in which the risk factors follow diffusions, jump-diffusion, or have “switching regimes.” Then the goodness-of-fit of these models is assessed relative to their abilities to (i) match linear projections of changes in yields onto the slope of the yield curve; (ii) match the persistence of conditional volatilities, and the shapes of term structures of unconditional volatilities, of yields; and (iii) to reliably price caps, swaptions, and other fixed-income derivatives. For the case of defaultable securities we explore the relative fits to historical yield spreads.