Financial Factors and Their Relative Importance Analysis in Peruvian Gold Mining Companies’ Stock Price
Bibliographic record
Abstract
The current research examined the relationship and relative importance of financial regressors on Peruvian gold mining companies´ stock prices from 2009 to 2018. Chosen regressors were earnings per share, dividend per share and dividend yield. Fixed effects analysis was employed for regression analysis and decomposition for the relative importance study. Assumptions of stationarity, independence, no-multicollinearity, homoscedasticity and specification were fulfilled. Also, the values of Owen and Shapley were employed for decomposing . It was found that earnings per share and dividend per share had a positive effect on the dependent variable; while dividend yield was found to be negatively related to stock price. Moreover, by the usage of decomposition it was noticed that the order of regressors importance was earnings per share, dividend per share and dividend yield. Then, it was stated that gold mining stock prices had a high dependence on profits and dividend payments in the analyzed period which can be related to the bearer’s expectations.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".