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Record W2608644307 · doi:10.5539/ijef.v9n5p143

Financial Market Evaluative Inefficiencies and Companies Sub-Optimal Investment Choices: How to Get Out of the Shortermist Impasse?

2017· article· en· W2608644307 on OpenAlexvenueno aff
Bruna Ecchia

Bibliographic record

VenueInternational Journal of Economics and Finance · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsShareholderProfitability indexIncentiveLoyaltyInvestment (military)FinanceEconomicsBusinessMarket economyMarketingCorporate governance

Abstract

fetched live from OpenAlex

This paper examines, in an innovative way as compared to the literature on the subject, “whether, how and under what conditions” certain technical devices, such as so-called “loyalty bonuses,” devised to increase the holding period of shares, can effectively reach their goal of countering the short-termist tendency involved in company investment decisions. This trend is an expression of compliance toward the current short-termism of the financial market as evidenced by the enormous shortening of the average share-holding period. This is not a recent phenomenon but it becomes more marked in times of crisis. Thus many projects, although functional to a company’s competitiveness, are rejected simply because of their deferred profitability and therefore incompatibility with the short market horizon, more focused on results emerging from quarterly reports than on a company’s long-term choices for business development. If the market is unable to immediately and adequately incorporate into prices the benefits from deferred returns, shareholders can equally obtain them if they remain durably connected with the company, but this choice must be encouraged by appropriate incentives. The loyalty bonus may be useful for this purpose and for long-term company interests, because it contributes to a better alignment of shareholders’ expectations with a more long-term vision in investment strategy. However the bonus, rather than involving the minority shareholders in the enterprise’s “mission,” often degenerates into a Control Enhancing Mechanism, though with unusual effects, among which a situation of “captivity” for all shareholders, even and especially the majority shareholders. In any case the utility of the bonus can occur, especially in less efficient markets. In a fully efficient market it could be harmful.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.006
Scholarly communication0.0050.010
Open science0.0010.002
Research integrity0.0010.002
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 head0.026
GPT teacher head0.243
Teacher spread0.217 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

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