A frequency decomposition of approximation errors in stochastic discount factor models

This paper extends the work of Hansen and Jagannathan (1997) by showing how to decompose approximation errors in stochastic discount factor models by frequency. This decomposition is applied to a number of prominent consumption-based discount factor models top 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.