Working Paper: CEPR ID: DP16109
Authors: Simon Smith; Allan Timmermann
Abstract: We apply a new methodology for identifying pervasive and discrete changes (``breaks'') in cross-sectional risk premia and find empirical evidence that these are economically important for understanding returns on US stocks. Size and value risk premia have fallen off to the point where they are insignificantly different from zero at the end of the sample. The market risk premium has also declined systematically over time but remains significant and positive as does the momentum risk premium. We construct a new instability risk factor from cross-sectional differences in individual stocks' exposure to time-varying risk premia and show that this factor earns a premium comparable to that of commonly used risk factors. Using industry- and characteristics-sorted portfolios, we show that some breaks to the return premium process are broad-based, affecting all stocks regardless of industry- or firm characteristics, while others are limited to stocks with specific style characteristics. Moreover, we identify distinct lead-lag patterns in how breaks to the risk premium process impact stocks in different industries and with different style characteristics.
Keywords: Cross-sectional variation in risk premia; Instability risk factor; Industry and style portfolios; Bayesian analysis
JEL Codes: G10; C11; C15
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| size and value risk premia (G11) | levels that are insignificantly different from zero (C12) |
| breaks in the risk premium process (G19) | significant transformation in the risk premium landscape (G19) |
| exposure to instability risk (F65) | higher returns (G12) |
| momentum risk premium recovery (G19) | contradicting trends observed in other risk factors (D91) |
| regime shifts (P39) | risk premia (G22) |
| break risk factor (J26) | premium comparable to traditional risk factors (G52) |