Bibliographic record
Abstract
In the first quarter of 2020, the global stock markets were hit by the COVID-19 pandemic and consequently experienced a sharp crash. This thesis examines the effect of corporate social responsibility (CSR) on Nordic stocks’ returns during the crisis induced market crash and the following recovery. In line with the literature, the level of CSR is proxied by firm-specific Environmental, Social, and Governance (ESG) scores provided by LSEG Thomson Reuters. The role of CSR has been growing in investment allocations, as shown by the rising amount of sustainable funds under management. Furthermore, this thesis focuses on Nordic markets, which are homogenous and characterized as high-trust societies. In high-trust societies the role of social responsibility is pivotal. Given the exogenous nature of the COVID-19 crisis shock on the markets, it offered an opportunity to investigate if Nordic markets trust the corporations with higher levels of CSR and those companies would then perform better during the crisis. The empirical part of the study examines 279 Nordic stocks’ returns in the crisis period from 20th of February to 23rd of March and post-crisis period from 24th of March to 5th of June. The stock returns are controlled for with firm-specific characteristics. Industries and Fama-French three factor model are also controlled for. Multiple different model specifications are run, but there is no evidence that ESG scores affected stock returns during the COVID-19 period. However, there is weak evidence of higher Environmental pillar score being associated with lower post crisis period returns. The results suggest that CSR did not protect stock prices from the COVID-19 shock in Nordics. The study hints at ESG metrics being possibly poor predictors of crisis resilience in Nordic region during crises, but it is not possible to draw too far-reaching conclusions about the link in future crises. Finally, this thesis provides practical insights for investors, managers and policymakers dealing with CSR-related 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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; both teacher heads agree on what is shown here.
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".