Predicting Long-Run and Short-Run Movement of Sectoral Index: Evidence From Philippine Stock Market
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 financial markets provide a viable avenue for investors who wants to invest their idle resources. Investors need accurate information to minimize investment risk and make the right investment decision. This study attempted to test the predictability of the Philippine Stock Exchange (PSE) sectoral indices. The data used in this study are the daily closing price of the six sectoral indices from January 2010 to December 2019. Augmented Dickey-Fuller (ADF) for stationarity test and Johansen Cointegration and Granger Causality analysis were used to test the long-run and short-run relationship among the six sectoral indices. The results showed that all indices are not predictable at the index level (I(0)) but predictable at the first difference (I(1)). The study found no long-run relationships between sectoral indices. The result also revealed that the sectoral indices have a short-run relationship in both directions.
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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 | 0.031 | 0.118 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it