A frequency decomposition of approximation errors in stochastic discount factor models

This article extends the work of Hansen and Jagannathan by showing how to decompose approximation errors in stochastic discount factor models by frequency. This decomposition is applied to a number of consumption-based discount factor models in order to investigate how well they fit at low frequencies. There is some evidence of improved fit at low frequencies, but only in models with high degrees of risk aversion. In models with low degrees of risk aversion, approximation errors at low frequencies are just as severe as those at high frequencies.