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Institutional Investment Horizons and the Cost of Equity Capital

2012· article· en· W3121857641 on OpenAlexaff
Najah Attig, Sean Cleary, Sadok El Ghoul, Omrane Guedhami

Bibliographic record

VenueFinancial Management · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsInstitutional investorEquity (law)Agency costInvestment (military)Cost of capitalEquity capital marketsCost of equityEconomicsClub dealEquity riskPrivate equity fundBusinessNew horizonsPrivate equity firmMonetary economicsFinanceFinancial economicsPrivate equityMicroeconomicsCorporate governanceShareholder

Abstract

fetched live from OpenAlex

We examine the influence of institutional investors’ investment horizons on a firm's cost of equity. We argue that the cost of equity will decrease in the presence of institutional investors with longer‐term investment horizons due to improved monitoring and information quality. Our empirical results demonstrate that the cost of equity declines in the presence of institutional investors with long‐term investment horizons, all else remaining equal. Our results indicate also that the monitoring role of long‐term institutional investors is more pronounced for firms with higher agency problems (poorly governed firms). Overall, our evidence suggests that when considering the influence of institutional investors, it is critical to account for institutional heterogeneity, which leads to new directions for future research.

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)0.014
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.014
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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.222
Teacher spread0.201 · 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

Citations136
Published2012
Admission routes1
Has abstractyes

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