Earnings Management Effect In Different Stock Market Cycles
Bibliographic record
Abstract
<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">This study examines the association between stock prices and discretionary accruals in different stock market cycles. The study presents evidence for a discrepancy in prior research and shows that investors are able to identify earnings management only in some cases. We argue that investors&rsquo; reaction to the true nature of EPS varies in different market cycles. We suggests that investors pay less attention to the nature of EPS changes in an optimistic cycles, and are more critical in neutral or pessimistic cycles. Therefore, investors are more likely to detect and count for any earnings management in the neutral or pessimistic cycle than in the optimistic cycle. The test results indicated that the association between discretionary accruals and abnormal stock returns were insignificant in the neutral market cycle, significant and positive in the optimistic cycle and significant and negative in the pessimistic cycle. These findings indicate that investors tend to ignore the income-increasing effect of discretionary accruals on EPS changes in an optimistic market. The findings suggest that researchers investigating the association between stock prices and earnings management should control for the type of the market cycle from which their samples are drawn. </span></span></p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".