Multi-Scaling Analysis of the S&P500 under Different Regimes in Wavelet Domain
Why this work is in the frame
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Bibliographic record
Abstract
In this article, the authors investigate the multi-scale structure of the S&P500 minute-by-minute time series. The authors attempt to find the answer to the following question: Are upward and downward regimes in the S&P500 time series exhibit different long-range power-law correlations? To answer this question, the authors apply the discrete wavelet transform (DWT) to the original time series for de-noising purpose. Then, the authors apply the generalized Hurst exponent (GHE) to the de-noised data to characterize the multi-scaling complexity of the signal (time series) under each regime and using different q-order moments. The authors found that S&P500 intra-day time series show long-range power-law correlations. In addition, this behavior varies depending on the stock market regime. This finding should be taken into account in active investment management.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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