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Performance of Social Pillar-Based Portfolio in Developing Capital Market

2022· article· en· W4312165846 on OpenAlexaboutno aff
Jovica Stanković, Ksenija Denčić-Mihajlov, Jelena Stanković, Evica Petrović

Bibliographic record

VenueManagement Journal of Sustainable Business and Management Solutions in Emerging Economies · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSustainable Finance and Green Bonds
Canadian institutionsnot available
Fundersnot available
KeywordsPortfolioStock exchangeBusinessCapital marketCapital market lineFinancial marketInvestment strategyFinancial economicsAsset allocationSocial capitalVolatility (finance)Stock marketFinanceMarket liquidityEconomicsMarket depth

Abstract

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Research Question: This study examined the preconditions and efficiency of socially responsible investing (SRI) in the developing capital market, specifically the Belgrade Stock Exchange (BSE). Motivation: Considering the increasing trend of SRI (GSIA, 2020) and importance of information on corporate social responsibility (CSR) to investors (Miralles‐Quiros, Miralles‐Quiros, & Arraiano, 2017), especially on social issues (Giese, Nagy, & Lee, 2021), we explored the influence of applying the social criteria in asset selection on investment portfolio performance at the BSE. This study builds on the existing literature that is mostly focused on developed capital markets of Europe, the United States and Canada (Von Wallis & Klein, 2015) by analysing the issue of SRI in the developing market. The provided setup for socially driven portfolio structuring based on market trends and social performance disclosure proved to be efficient in the long-term. Idea: The core idea of this paper was to analyse the terms for SRI and empirically evaluate the performance of social pillar-based portfolio on the BSE in order to provide evidence to support the trend of SRI in developing markets. The structure of the portfolios was set using the best-in-class strategy, while the classes were determined on the basis of the stocks’ return trends. Data: The analysis was conducted using trading data and information from financial and non-financial reports of the companies listed on the BSE. Tools: Cluster analysis was used for classification of stocks, while performances of portfolios were evaluated implementing return, volatility and risk-adjusted measures. Findings: The social pillar-based portfolio outperformed the conventional one and benchmarking indices in the observed five-year period. However, mixed results were obtained in the short-term indicating that specific effects of CSR practice on financial performance of the companies in observed developing market could still be obscured. Contribution: This paper expands the existing research related to SRI in the developing markets and offers practical recommendations for potential socially conscious investors.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.206
Teacher spread0.192 · 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 teacher head, not a consensus.

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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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