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Record W2125647111

The Valuation Effect of Listing Requirements: An Analysis of Venture Capital-Backed IPOs

2010· preprint· en· W2125647111 on OpenAlexfundaboutno aff
Cécile Carpentier, Douglas J. Cumming, Jean‐Marc Suret

Bibliographic record

VenueÉrudit documents and data repository (Érudit Consortium, University of Montreal) · 2010
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInitial public offeringListing (finance)Valuation (finance)Market liquidityVenture capitalPolitical scienceEconomicsHumanitiesWelfare economicsMonetary economicsFinance
DOInot available

Abstract

fetched live from OpenAlex

Ce papier examine l'impact de la réglementation des valeurs mobilières et des normes minimales d'inscription en bourse sur la valorisation des premiers appels publics à l'épargne (PAPEs) effectués au Canada et aux États-Unis par des émetteurs financés par des investisseurs en capital de risque. Nous utilisons un échantillon de PAPEs dans chacun des pays sur la période 1986 à 2007. Chaque émission canadienne est pairée avec une émission américaine de taille et de secteur similaires. Nous montrons que les valorisations des émissions canadiennes sont de 48 % à 66 % plus basses que celles des émissions correspondantes américaines, en fonction de l'échantillon retenu et des variables de contrôle. Cette différence subsiste à la prise en compte de plusieurs variables de contrôle, notamment la qualité des émetteurs et des investisseurs en capital de risque, ainsi que la liquidité. Les résultats montrent que les normes réglementaires permissives appliquées aux entreprises émergentes au Canada ont un effet perceptible sur la valeur que leur attribuent les investisseurs.

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)0.004
metaresearch head score (Gemma)0.017
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 score0.120
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.019
GPT teacher head0.251
Teacher spread0.232 · 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

Citations6
Published2010
Admission routes2
Has abstractyes

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Same venueÉrudit documents and data repository (Érudit Consortium, University of Montreal)Same topicPrivate Equity and Venture CapitalFrench-language works237,207