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Record W3217421076 · doi:10.3390/jrfm14120569

The Role of Investor Relations and Good Corporate Governance on Firm Performance in the Case of the Companies Listed on the Bucharest Stock Exchange

2021· article· en· W3217421076 on OpenAlexvenueno aff
Bogdan Aurelian Mihail, Dalina Dumitrescu, Daniela Șerban, Carmen Daniela Micu, Adriana Lobda

Bibliographic record

VenueJournal of risk and financial management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsStock exchangeInvestor relationsBusinessMarket liquidityCorporate governanceValuation (finance)AccountingFinancial economicsEconomicsFinanceMarketingStrategic management

Abstract

fetched live from OpenAlex

The objective of this paper is to investigate the role of Investor Relations (IR) in the performance of companies listed on the Bucharest Stock Exchange. The study is motivated by the findings in the literature that investor relations may boost information disclosure, analyst following, institutional investor share, liquidity, and business valuation. The current article contributes to the relevant literature by making use of the recently released unique database of VEKTOR scores on company investor relations for 2019 and 2020. The main finding based on regression methodology shows that IR scores have a strong positive relationship with firm performance. Specifically, a one standard deviation rise in the IR score corresponds to a 2.6% rise in company ROA. Companies may be advised to strengthen their investor relations based on these findings about the beneficial role of investor relations.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.191
Teacher spread0.173 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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