Working Paper: NBER ID: w9143
Authors: Wayne E. Ferson; Sergei Sarkissian; Timothy Simin
Abstract: Even though stock returns are not highly autocorrelated, there is a spurious regression bias in predictive regressions for stock returns related to the classic studies of Yule (1926) and Granger and Newbold (1974). Data mining for predictor variables interacts with spurious regression bias. The two effects reinforce each other, because more highly persistent series are more likely to be found significant in the search for predictor variables. Our simulations suggest that many of the regressions in the literature, based on individual predictor variables, may be spurious
Keywords: No keywords provided
JEL Codes: G10; G12; G14; C10; C12; C22
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| persistent expected returns (G17) | spurious regression (C29) |
| spurious regression (C29) | significant regression results (C29) |
| data mining (C55) | spurious regression (C29) |
| persistent expected returns (G17) | significant regression results (C29) |