Working Paper: NBER ID: w19416
Authors: Ian Dewbecker; Stefano Giglio
Abstract: In affine asset pricing models, the innovation to the pricing kernel is a function of innovations to current and expected future values of an economic state variable, for example consumption growth, aggregate market returns, or short-term interest rates. The impulse response of this priced variable to fundamental shocks has a frequency (Fourier) decomposition, which captures the fluctuations induced in the priced variable at different frequencies. We show that the price of risk for a given shock can be represented as a weighted integral over that spectral decomposition. The weight assigned to each frequency then represents the frequency-specific price of risk, and is entirely determined by the preferences of investors. For example, standard Epstein-Zin preferences imply that the weight of the pricing kernel lies almost entirely at extremely low frequencies, most of it on cycles longer than 230 years; internal habit-formation models imply that the weight is shifted to high frequencies. We estimate the frequency-specific risk prices for the equity market, focusing on economically interesting frequencies. Most of the pricing weight falls on low frequencies - corresponding to cycles longer than 8 years - broadly consistent with Epstein-Zin preferences.
Keywords: Asset Pricing; Frequency Domain; Risk Prices
JEL Codes: E21; G10; G12
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| price of risk for a shock (D81) | weighted integral over its spectral decomposition (C51) |
| weighted integral over its spectral decomposition (C51) | frequency-specific price of risk (G19) |
| investor preferences (G11) | frequency-specific price of risk (G19) |
| long-term risks (I12) | influence asset pricing (G19) |
| short-term fluctuations (E32) | significant for agents with internal habit-formation models (C69) |
| dynamic response of consumption growth to shocks (E20) | pricing kernel's innovations (D49) |
| interaction between impulse transfer function and investor preferences (G40) | understanding dynamics of asset pricing (G19) |
| shocks defined in terms of cycles longer than the business cycle (E32) | support long-run risk models (C58) |
| covariance with long-run shocks (C10) | statistically significant determinant of average portfolio returns (G11) |