Working Paper: NBER ID: w12658
Authors: Wayne E. Ferson; Sergei Sarkissian; Timothy Simin
Abstract: This paper studies the estimation of asset pricing model regressions with conditional alphas and betas, focusing on the joint effects of data snooping and spurious regression. We find that the regressions are reasonably well specified for conditional betas, even in settings where simple predictive regressions are severely biased. However, there are biases in estimates of the conditional alphas. When time-varying alphas are suppressed and only time-varying betas are considered, the betas become baised. Previous studies overstate the significance of time-varying alphas.
Keywords: asset pricing; conditional betas; conditional alphas; data snooping; spurious regression
JEL Codes: C5; G1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| data mining (C55) | biases in estimating conditional alphas (C51) |
| data mining (C55) | biases in estimating conditional betas (C46) |
| suppressing time-varying alphas (C22) | biases in estimates of conditional alphas (C51) |
| suppressing time-varying alphas (C22) | biased beta estimates (C51) |
| average conditional alphas over time are well specified (C51) | time variation in alpha inherits biases (C22) |
| joint effects of data mining and spurious regression (C29) | affect inferences drawn from models (C20) |
| time-varying alphas (C22) | overstated significance in literature (Y30) |