Evidencia De Comportamiento Caótico En Indices Bursátiles Americanos
Bibliographic record
Abstract
This article validates the chaotic behavior in the Argentinean, Brazilian, Canadian, Chilean, American, Peruvian and Mexican Stock Markets using the MERVAL, BOVESPA, S&P TSX COMPOSITE, IPSA, IGPA, S&P 500, DOW JONES INDUSTRIALS, NASDAQ, IGBVL and IPC Stock Indexes respectively. The results of different techniques and methods like: Graphic Analysis, Recurrence Analysis, Temporal Space Entropy, Hurst Coefficient, Lyapunov Exponential and Correlation Dimension support the hypothesis that the stock markets behave in a chaotic way and rejected the hypothesis of randomness. Our conclusion validates the use of prediction techniques in those stock markets. It’s remarkable the result of the Hurst Coefficient Technique, that in average was of 0,75 for the indexes of this study which would justify the use of ARFIMA models among others for the prediction of such series.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".