Verifying Capital Asset Pricing Model in Greek Capital Market
Bibliographic record
Abstract
This article deals with capital asset valuation on Greek capital market using Capital Asset Pricing Model (CAPM). We examined 32 companies listed on the Athens Stock Exchange on a weekly basis for a period from June 2009 to December 2013 under this model. The CAPM model is tested by performing two-pass characteristic regression analyses. The first-pass characteristic line regression was used to estimate stocks of beta. Hence, the second-pass characteristic line regression was taken to analyze the intercept and the slope coefficients of stocks. The two characteristics of line regression verify the adequacy of the CAPM. According to our results, we came to a conclusion that there was a linear relationship between systematic risk and returns. The CAPM would be the verification of our major hypotheses from the time series tests. In order for this to be true, the intercept ought to be approximately equal to zero, supporting the theories for both individual assets and portfolios. However, the testing provides evidence against the CAPM, but do they do? It should be kept in mind that it does not necessarily represent evidence in favor of any alternative model.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".