Abstract:
This paper proposes a novel derivation of the Hodrick-Prescott (HP) minimization problem which
leads to a generalization of the Hodrick-Prescott filter. The main result is the development of a new filter to
extract a localized maximum-likelihood estimate of the cycle from a series. This new filter, the multivariate
normal cyclical (MNC) filter, makes only a general assumption about the cyclical nature of the series. The
output from this filtering procedure is from a nonlinear optimization routine.
