Financial Contagion Patterns in Individual Economic Sectors. The Day-of-the-Week Effect from the Polish, Russian and Romanian Markets
Bibliographic record
Abstract
This paper studies the presence of the day-of-the-week (DOW) effect in the financial contagion process observed on individual economic sectors from the Post-Communist East European markets. The only markets that provide national-specific sector indices determined throughout the 2008 financial crisis are Poland, Romania and Russia. The novel methodology combines two existing perspectives from financial literature, by employing a GJR-GARCH framework on a dummy regression model that accounts for both the crisis period and the weekdays. All indices show the presence of the DOW effect during the crisis and/or non-crisis periods, thus signaling their low level of market efficiency. However, the contagion process affects only eight of these indices: the banking, IT and oil and gas sectors from Poland, the chemical, telecommunication and transport sectors from Russia and energy sectors from Russia and Romania. All of them show signs of the DOW effect in contagion: five exhibit higher spillovers on crisis Mondays, while the other three show other weekday patterns. The findings suggest that the DOW effect is not specific to certain countries or certain economic sectors.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".