Investment Recommendations Made by Financial Analysts and Their Impact upon the Price Evolution of the Shares Listed on the Bucharest Stock Exchange
Bibliographic record
Abstract
The investment decisions made by investors on the capital market are based, among others, on the recommendations made by financial analysts. The extent to which investors take into consideration the investment recommendations made by the analysts differs mainly due to the degree of the capital market development, the role it plays in financial intermediation process and the informational efficiency of the market. Based on the data collected on the Bloomberg platform, we analyzed to what extent the stock exchange evolution trend (increase or decrease) overlaps the trend forecasted by the analysts. Thus, we test whether the increase/decrease estimated by the analysts matched the stock exchange evolution in the following quarter of the recommendation announcement, without highlighting the level of the recorded increase/decrease. Also, we compared the estimated potential upside/downside against the percentage change of the average price in the quarter following the recommendation announcement compared with the price recorded on the day of recommendation.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".