Corporate Social Responsibility & Market Volatility: Relationship and Trading Opportunities
Bibliographic record
Abstract
This article examines the relationship between corporate social responsibility performance (CSR.P) and market trading volatility (MTV) provoking by the release of the non-farm employment payment-reports (NFP) the first Friday each month in the USA. It also discusses the trading opportunities involved in such as volatile environments. Actually, we consider the interaction between the social performance (for environment, employment and community activities) and the financial and trading performance than would be the case for an accumulated functionality in NFP releases. In general, social performance returns are negatively related to trading returns; so, the relatively poor financial and market trading reward (profit), offered by socially responsible ethical ETFs trading the NFP reports, is in accordance to their good social performance regarding employment and environmental aspects. This could be changed if these ethical ETFs incorporate into their arsenal of trading tools a number of CSR.mtv functions (utilities) discussed in this article. Impressively, we find also that considerable bizarre returns are obtained by funds, holding a portfolio of socially least unethical ETFs, involved in short-term or intraday speculations. In this domain, the complex relationship between social, financial and market trading performance, during the NFP “psychological time”, offers great trading opportunities.
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".