MétaCan
Menu
← Back to cohort
Record W4407088845 · doi:10.3390/jrfm18020071

The Big Three Passive Investors and the Cost of Equity Capital

2025· article· en· W4407088845 on OpenAlexvenueno aff
Sebahattin Demirkan, Ted M. Fikret Polat

Bibliographic record

VenueJournal of risk and financial management · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsCost of capitalEquity capital marketsEquity (law)BusinessCapital (architecture)Monetary economicsCost of equityEconomicsFinanceFinancial systemFinancial economicsPrivate equityMicroeconomicsArtPolitical science

Abstract

fetched live from OpenAlex

This study investigates the role of the Big Three passive investors (BlackRock, Vanguard, and State Street) in influencing firms’ cost of equity. By examining the unique ownership structure these investors bring, the research sheds light on a pivotal yet underexplored aspect of institutional ownership and its implications for corporate financing. Using a comprehensive dataset spanning from 1997 to 2016, this study demonstrates that increased ownership by the Big Three is associated with improved disclosure practices and reduced information asymmetry, leading to a lower cost of equity. However, the study also uncovers a nuanced trade-off, as concentrated ownership may introduce liquidity risks in certain contexts. These findings bridge a critical gap in the literature by reconciling divergent perspectives on the role of passive investors and provide actionable insights for institutional investors, regulators, and corporate managers seeking to understand the broader implications of passive ownership on firm valuation and financing strategies.

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)0.010
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.215
Teacher spread0.198 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of risk and financial management→Same topicFinancial Markets and Investment Strategies→French-language works237,207→