STUDY ON THE FRACTAL AND CHAOTIC FEATURES OF THE SHANGHAI COMPOSITE INDEX
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Hurst exponent derived by the R/S analysis method of Shanghai stock market's logarithmic return series is about 0.6298. This shows that the Shanghai stock market exhibits fractal features, and a long memory cycle of about one-and-a-half years. With the reconstruction of phase space, the Shanghai Stock attractor dimension converges to 1.335, which means that the Shanghai stock market has chaotic features, and constructing a dynamic system of the Shanghai stock market needs at least two variables. The findings from the principal component analysis support the conclusion of the existence of chaotic features of the Shanghai stock market. The fractal and chaotic features of the Shanghai stock market reveal the nonlinear properties of the Chinese stock market, and the nonlinearity perspective will be more conducive to the formulation of countermeasures for the development of the Chinese stock market.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it