Determination of the Fractal Character of the Romanian Capital Market by Using Hurst Exponent
Bibliographic record
Abstract
Failure of classical statistical methods to model the behavior of stock market prices determined, in a domino effect, the failure of the classical paradigm of regarding markets as efficient systems. Alternative to this simple interpretation, markets should be regarded as far from equilibrum dynamical systems, complex evolving structures that encompass millions of participants, holding into their memory events that happened long time ago. This more realistic approach was developed by Fractal Market Hypothesis, as an alternative to Efficient Market Hypothesis. R/S Analysis is a robust tool for testing whether markets follow a Brownian motion or some memory effect is implied. The aim of the paper is to determine the Hurst Exponent, for company ALRO S.A., for the period of time since listing, until 16/07/2021. Results may generate indications about in the nature of the system represented by the prices of ALRO S.A. Conclusion may be that the Romanian capital market, as ALRO is one of the most representative companies listed at Bucharest Stock Exchange, has evolved from a very low stability market to a more stable investment environment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".