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Record W3124823076

On the Performance of Socially Responsible Investing: Further Evidence

2012· article· en· W3124823076 on OpenAlexaff
Homayoon Shalchian, Bouchra M’Zali, JJ Lilti, Khalid Elbadraoui

Bibliographic record

VenueMunich Personal RePEc Archive (Ludwig Maximilian University of Munich) · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSocially responsible investingEquity (law)Corporate social responsibilityEmpirical evidenceStock marketEconomicsSocial responsibilityRelation (database)Stock (firearms)Financial economicsBusinessFinancePolitical scienceCorporate governance
DOInot available

Abstract

fetched live from OpenAlex

We examine the relation between corporate social performance and stock portfolios performances. Based on Kinder, Lydenberg and Domini social performance ratings, the study constructs and evaluates different sets of equity portfolios that differ in social performance. The high-ranked portfolios provide, in most cases, higher average returns than their low-ranked counterparts over the 1995-2006 period. In addition, we observe that the relation social-financial performance depends also on the economic cycle and consequently, on the market performance. Socially responsible investments seem to be more popular during bearish market periods and less popular during bullish market periods. Finally, our results suggest that in some industries, the differences of performances are more significant than in others. In other words, the relation social-financial performance seems to be considerably affected by the nature of firms’ activities. Therefore, our empirical results suggest that industry is an important factor that should be taken in consideration in studies on the relation between social and financial performance

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.043
GPT teacher head0.206
Teacher spread0.162 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2012
Admission routes1
Has abstractyes

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