A frequency decomposition of approximation errors in stochastic discount factor models

This article extends the work of Hansen and Jagannathan by showing how to d ecompose approximation errors in stochastic discount factor models by frequ ency. This decomposition is applied to a number of consumption-based discou nt factor models in order to investigate how well they fit at low frequenci es. 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 ri sk aversion, approximation errors at low frequencies are just as severe as those at high frequencies.