Analysis of Co-Movements in Ecowas Financial Markets of Oil Importing and Exporting Countries and the Price of Brent: A Wavelet Approach
Bibliographic record
Abstract
The objective of this paper is to analyze the effects of contagion, interdependence, and changes in the correlation structure, after the COVID-19 crisis, on the financial markets of the ECOWAS oil importing and exporting area and the price of BRENT. To do this, two wavelet approaches in a time-frequency domain (the local correlation wavelet (WLC) and the correlation wavelet (WC)), on daily data from January 04, 2005, to January 06, 2022, of the composite indices of the NSE, the BRVM, the GSE and the price of BRENT, are mobilized. The results mainly reveal the existence of contagion and co-movement on the one hand, and variation in the correlation structure in the post-COVID-19 era on the other. The study thus exhibits evidence of the coexistence of contagion, co-movement, and permanent change in the correlation structure between the ECOWAS financial markets and the price of BRENT before and after the COVID-19 crisis.
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.
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 | 0.002 |
| 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".