The Relationship between Earnings and Stock Returns: Empirical Evidence from the Greek Capital Market
Bibliographic record
Abstract
The relationship between earnings figures and stock returns has been a topic of international research since decades. The purpose of this paper is to investigate the above relationship in the context of the Greek capital market. Previous studies resulted in controversial results regarding the usefulness of models which were using earnings levels or earnings changes as the explanatory variable. In an introductory context, this study examines the earnings-return relation applying four models, proposed by Kothari and Zimmerman (Journal of Accounting and Economics, 20, 155-192, 1995), on individual Greek stocks as well as portfolios between 1994-2004. The overall results, demonstrated a significant value relevancy of accounting earnings prepared under the Greek GAAP. Specifically in the Greek stock market the price model produces less biased ERC’s than the return model but suffers from various econometric problems. Also, the use of cross-sectional and time-series aggregated data results in a large increase in the explanatory power of earnings for returns (for the return and differenced model) yielding more significant Earnings Response Coefficients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".