MétaCan
Menu
Back to cohort
Record W3092200542 · doi:10.5430/ijfr.v11n5p424

The Relationship Between of Cash Flows (Financing, Investment and Operating) and Stock Prices, Size of the Firms

2020· article· en· W3092200542 on OpenAlexvenueno aff
Tamer Bahjat Sabri, Khalid Sweis, Issam Ayyash, Yasmeen Faheem Asaad Qalalwi, Israa Sami Abbas Abdullah

Bibliographic record

VenueInternational Journal of Financial Research · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
FundersPalestine Technical University Kadoorie
KeywordsNull hypothesisStock exchangeCash flowOperating cash flowStock (firearms)Growth stockBusinessStatistical hypothesis testingEconomicsFinanceEconometricsFinancial economicsRestricted stockMathematicsStatisticsStock market

Abstract

fetched live from OpenAlex

This study sought to test the relationship between cash flows from operating activities, investment activities and financial activities and on one hand and stock returns and the volume of assets on the companies listed in Palestine Stock Exchange on the other hand. The study incorporated 24 companies in 2018 and the required data were obtained through the financial statements. To test the hypotheses of the study, the Mann-Whitny U Test was used, a nonparametric test. Also the Kolmogorov-Smirnov was done. The findings demonstrated that the value of the Whitny U Test was (-3.291) Z with a statistical significance at 1%. Based on this, the null hypothesis was rejected and the alternative one, stating that there is a statistically significant difference between the operating flows of companies with low assets and those companies with high assets, was accepted. However, the other null hypothesis was accepted. The study recommended that companies and investors should take into consideration cash flows when taking an investment decision in Palestine Stock Exchange.

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)0.006
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.060
GPT teacher head0.319
Teacher spread0.259 · 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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Financial ResearchSame topicAuditing, Earnings Management, GovernanceFrench-language works237,207