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Record W2109235069 · doi:10.5539/ibr.v6n6p1

Division Buyout and Refinancing of Event Risk Covenant Bonds: Evidence from the Long-Term Stock Performance

2013· article· en· W2109235069 on OpenAlexvenueno aff
Manish Tewari

Bibliographic record

VenueInternational Business Research · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsBondMonetary economicsVolatility (finance)Event studyBusinessLeveraged buyoutStock (firearms)Cash flowDivestmentEquity (law)EconomicsShareholderFinancial economicsFinanceCorporate governancePrivate equity

Abstract

fetched live from OpenAlex

The focus of this paper is to assess the long-term common stock performance of the parent firms that underwent divisional buyout (DBO) and had event risk covenant (ERC) bonds outstanding at the announcement of the DBO. The final sample of 46 parent firms exhibit a common characteristic where all the ERC bonds were redeemed (either called above par or put on the firm at par) or restructured at a higher cost to the firm around DBO announcement date due to the presence of ERCs. ERCs are triggered since the parent firms that divest their assets through a DBO reveal future cash flow volatility, which has potential to lower the value of existing bonds. This refunding of the bonds leads to costly refinancing for the parent firms, which has long-term implications. I find significantly negative cumulative abnormal returns at the issue date of the ERC bonds for these firms due to potential managerial entrenchment and foregone transfer of wealth from bondholders to stockholders. Consistent with the finance literature, I find significantly positive cumulative abnormal returns for parent firms at the announcement of the DBO. These positive short-term returns at the announcement do not translate into long-term positive returns. The common stock of these parent firms significantly underperforms the market over the periods three, four, and five years after the DBO date. This dichotomy can be attributed to the security market overreaction to the announcement of DBO. The long-term underperformance can be attributed to the costly refinancing of the ERC bonds.

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 score0.004
Threshold uncertainty score0.008

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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.317
Teacher spread0.254 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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