Detection of Structural Regimes and Analyzing the Impact of Crude Oil\n Market on Canadian Stock Market: Markov Regime-Switching Approach
Bibliographic record
Abstract
This study aims to analyze the impact of the crude oil market on the Toronto\nStock Exchange Index (TSX)c based on monthly data from 1970 to 2021 using\nMarkov-switching vector autoregressive (MSI-VAR) model. The results indicate\nthat TSX return contains two regimes, including: positive return (regime 1),\nwhen growth rate of stock index is positive; and negative return (regime 2),\nwhen growth rate of stock index is negative. Moreover, regime 1 is more\nvolatile than regime 2. The findings also show the crude oil market has\nnegative effect on the stock market in regime 1, while it has positive effect\non the stock market in regime 2. In addition, we can see this effect in regime\n1 more significantly in comparison to regime 2. Furthermore, two period lag of\noil price decreases stock return in regime 1, while it increases stock return\nin regime 2.\n
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".