Determination of the Fractal Character of the Romanian Capital Market by Using Hurst Exponent
Bibliographic record
Abstract
\nFailure of classical statistical methods to model the behavior of stock market prices\ndetermined, in a domino effect, the failure of the classical paradigm of regarding markets as efficient\nsystems. Alternative to this simple interpretation, markets should be regarded as far from equilibrum\ndynamical systems, complex evolving structures that encompass millions of participants, holding into\ntheir memory events that happened long time ago. This more realistic approach was developed by\nFractal Market Hypothesis, as an alternative to Efficient Market Hypothesis. R/S Analysis is a robust\ntool for testing whether markets follow a Brownian motion or some memory effect is implied. The aim\nof the paper is to determine the Hurst Exponent, for company ALRO S.A., for the period of time since\nlisting, until 16/07/2021. Results may generate indications about in the nature of the system represented\nby the prices of ALRO S.A. Conclusion may be that the Romanian capital market, as ALRO is one of\nthe most representative companies listed at Bucharest Stock Exchange, has evolved from a very low\nstability market to a more stable investment environment.\n
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".