Determinants of Price to Earnings Multiple Around the World. Recent Findings
Bibliographic record
Abstract
This article deals with the functioning of capital markets, notably the impact of financial crisis on earnings’ pricing rationality. Through a global market based analysis it intends to test the effects of dividend ratios and other fundamentals on P/E multiple, in order to show some recent useful evidences. Starting from a classic theoretical premise (SHV Dividend Discount Model), the article sets out some consequent hypotheses and develops a linear multivariate econometric model to detect (for major quoted companies from US, Australia / New Zealand / Canada, Europe, Japan and Emerging Markets) the actual role of the most important relative valuation multiple determinants during a ‘critical period’. Indeed, the analysis refers to 2010, a peculiar year (immediately after the explosion of the Global Financial Crisis) which shows signals of both a weak recovery and a persisting uncertainty. Our findings, likely due to some distortions created by the crisis aftermath, do not fully confirm the SHV-DDM theoretical conjectures about the above said determinants. While the conjectured negative association between P/E and dividend yields seems to be confirmed, the positive association between P/E and payouts does not. Other relevant indicators (risk, roe/growth, leverage and corporate tax rate) are considered in the empirical model as control variables to complete the exploratory analysis. In sum, the paper may appear timely to ascertain the extent of the first and leading effects of the recent global crisis on the rational earnings’ pricing models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".