Mapping the Intellectual Structure of Asset Pricing: A Bibliometric Study
Bibliographic record
Abstract
This paper presents a bibliometric analysis of research on asset pricing and identifies and highlights the most significant authors, keywords, articles, and journals based on a systematic literature review and Bibliometric analysis of 915 documents published over 33 years (1989-2022), obtained from the web of science database, to discover the noticeable landscape and research horizons in the field of asset pricing theory. This descriptive study demonstrates an upward trend in ”asset pricing’ papers in business and finance journals. According to the report, the United States is the leading contributor to the ”asset pricing” study, followed by the Netherlands, the United Kingdom, Canada, and France. The authors, papers, and citation-based analyses show that Acharya vv; Albuquerque R, Aih, and Acciaio B are the most effective and influential asset pricing researchers, followed by Affleck Graves J and Akdeniz L. In terms of restrictions, our research is limited to the Web of Science database. Investigations from other databases could be used in future studies. We’ve also limited Bibliometric analysis to a few dimensions. Future research would look at networking from a different perspective. In our analysis, we limited ourselves to simply looking at scientific articles. Despite these flaws, we feel the study has research and management implications
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.017 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".