Abstract
This article estimates and employs low frequency components of asset returns and uses dynamic programming to evaluate dynamic consumption and asset allocation decisions. The low frequency components are estimated through fast Fourier transform (FFT). After harmonic fits of actual U.S. time series data using FFT, dynamic programming is used to solve for dynamic consumption and asset allocation decisions. Furthermore, dynamic consumption and asset allocation decisions are explored for varying risk aversions and varying time horizons across investors. The welfare of investors as well as the fate of their wealth is also explored. We also spell out some rough practical guidelines for financial investments for the case of time-varying asset returns.
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