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Record W1970389082 · doi:10.1108/sef-08-2013-0112

Is there a right time for corporate investment?

2014· article· en· W1970389082 on OpenAlexaff
Min Maung, Reza H. Chowdhury

Bibliographic record

VenueStudies in Economics and Finance · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsEquity (law)EconomicsEquity capital marketsShareholderMonetary economicsDebtCapital marketEquity riskMarket valueEquity ratioFinanceBusinessShareholder valueMarket timingFinancial economicsPrivate equityCorporate governanceInitial public offering

Abstract

fetched live from OpenAlex

Purpose – The purpose of this paper is to determine whether corporate investment in real fixed assets in hot issue markets leads to higher income to shareholders than that in other equity market conditions. Design/methodology/approach – The authors address the research question in two steps: first, the authors identify how security issuances in hot and cold issue markets influence corporate investment decisions. Second, the authors examine how debt- and equity-financed investments in two different market conditions affect future holding period returns. The sample includes an unbalanced panel data set consisting of all non-financial and non-utility US companies from 1973 to 2006. The authors apply both firm- and industry-level fixed effect methods to estimate the coefficients of two separate empirical models. Findings – The authors find that equity issuances increase firms' capital investments in hot issue markets. These equity-financed investments in hot equity markets result in higher returns to shareholders compared to those in other market conditions. Therefore, there exists a window of opportunity for firms to issue new equities and make investments, which in turn improve shareholders' wealth. Practical implications – The findings convey a critical message to corporate managers about the right timing of equity-financed capital investments. Originality/value – While earlier research focuses on determining a specific equity market condition that favours new issuances, this paper determines a particular equity market condition when firms typically choose value-enhancing equity-backed projects for investment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

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

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 head0.031
GPT teacher head0.219
Teacher spread0.188 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations5
Published2014
Admission routes1
Has abstractyes

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