The Impact of the Ukrainian Crisis and Global Shocks on Stock Market Connectedness in Sub-Saharan Africa: Evidence from Diebold and Yilmaz (2012) Spillover Analysis
Bibliographic record
Abstract
This study assesses the dynamic interconnectedness and transference of effects among burgeoning stock exchanges in Sub-Saharan Africa and between African and developed markets following the Ukrainian crisis in February 2022.In addition, the paper presents a comparative analysis of return and volatility during three distinct subperiods.These are the 2008 financial crisis, the COVID-19 pandemic in 2020, and the ongoing Ukrainian conflict.This paper conducts research using the Bai-Perron test for multiple structural breaks and the spillover index of Diebold and Yilmaz (2012), alongside the innovation accounting analysis test.The findings of this paper indicate that the resilience and isolation of stock markets in Africa to external financial shocks (volatility shock) have been weakened in the wake of the Ukrainian crisis and the COVID-19 pandemic as compared to the GFC sub-period.The results affirm that stock markets on the African continent have become more sensitive to structural changes and shocks in developed countries.This study has significant implications for investors and policymakers in Africa.Future investors need to genuinely diversify their investment portfolios to minimize future losses generated by shock transmission among markets.Policymakers might have to introduce fully fledged policies to diversify their economies and attract international investments.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".