Working Paper: CEPR ID: DP7656
Authors: Marco Aiolfi; Marius Rodriguez; Allan G. Timmermann
Abstract: This paper studies the asymmetric behavior of negative and positive values of analysts' earnings revisions and links it to the conservatism principle of accounting. Using a new three-state mixture of log-normals model that accounts for differences in the magnitude and persistence of positive, negative and zero revisions, we find evidence that revisions to analysts' earnings expectations can be predicted using publicly available information such as lagged interest rates and past revisions. We also find that our forecasts of revisions to analysts' earnings estimates help predict the actual earnings figure beyond the information contained in analysts' earnings expectations.
Keywords: analysts; earnings forecasts; mixture model; predictability of forecast revisions
JEL Codes: C22; G17
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Lagged interest rates (E43) | Revisions to analysts' earnings expectations (D84) |
| Past revisions (Y20) | Revisions to analysts' earnings expectations (D84) |
| Revisions to analysts' earnings expectations (D84) | Actual earnings figures announced by firms (G14) |
| Negative revisions occur more frequently than positive revisions (D91) | Greater volatility and persistence in negative revisions (E32) |
| Magnitude of negative revisions is significantly larger (C59) | Greater volatility and persistence in negative revisions (E32) |
| Negative news is fully declared while positive news is only partially declared (G14) | Greater volatility and persistence in negative revisions (E32) |