Book-to-Market and the Cross-Section ofExpected Returns in International Stock Markets
Bibliographic record
Abstract
Individual stocks’ expected return estimates are a key input for equity selection models. A 2008 study by Eugene Fama and Kenneth French found evidence that past changes in book equity and price contain independent information about expected cash flows that can be used to improve estimates of expected returns. This study focuses on international stock markets and re-examines whether the origins of the book-to-market ratio (BM), in terms of past changes in book equity and price, enhance the estimates of expected returns provided by BM alone. Examining all stocks, as well as subcategories of microcap, small, large, and all-butmicrocap stocks trading in the United Kingdom, Germany, France, Italy, Canada, and Japan, the authors find that recent changes in book equity and price are more relevant than more distant changes in enhancing estimates of expected future cash flows and expected future returns. Their tests also show that changes in book equity say much more about expected stock returns than price changes do. TOPICS:Global, exchanges/markets/clearinghouses, statistical methods
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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 | 0.011 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".