Bibliographic record
Abstract
Purpose The expected rate of return for individual firms is determined by multiple firm‐specific factors. There is no evidence on how firm life cycle contributes to the determination of the expected rate of return. This study explores how life cycle stage affects the expected rate of return. Design/methodology/approach Regression analysis is applied to observe the effect of life cycle. Expected rate of return is dependent variable. Life cycle measures are interacted with commonly identified risk factors. Empirical data was collected for publicly traded firms from COMPUSTAT. Findings The major finding of this study is the significant impact of life cycle stage. Results indicate that the value relevance of risk factors is conditional on firm life cycle stage. Findings suggest that capital markets do realize and incorporate information conveyed in firm life cycle stage when interpreting risk factors. Research limitations/implications Future research can explore effects of life cycle stage on share return volatility as investors trade off between return and risk. Originality/value This study targets a major aspect (i.e. what determine the expected rate of return in the finance literature) to shed light on the limited understanding of what contribute to individual firms’ risk premium. This study has implications for investor risk assessment and corporate risk management.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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, 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".