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Record W2307189401 · doi:10.5539/ijef.v8n4p63

The Effect of Liquidity on Financial Performance: Evidence from Turkish Retail Industry

2016· article· en· W2307189401 on OpenAlexvenueno aff
Kartal Demirgüneş

Bibliographic record

VenueInternational Journal of Economics and Finance · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsnot available
Fundersnot available
KeywordsMarket liquidityUnit root testEconometricsTurkishProfitability indexUnit rootStructural breakCointegrationCausality (physics)EconomicsSeries (stratigraphy)Granger causalityMonetary economicsFinancial economicsBusinessFinance

Abstract

fetched live from OpenAlex

The aim of this study is to analyse the effect of liquidity on financial performance (in terms of profitability) by using a time-series data of Turkish retail industry (consisting of Borsa Istanbul (BIST) listed retail merchandising firms) in the period of 1998.Q1-2015.Q3. The stationarity of series and the co-integration relationship between them are tested by the unit root test of Carrioni-i-Silvestre et al. (2009) and the co-integration test of Maki (2012), respectively. Co-integration coefficients are estimated by Stock and Watson (1993) dynamic OLS method. Finally, causal relationships between the series are tested by Hacker and Hatemi (2012) bootstrap causality test. Results of Maki (2012) test show that the series are co-integrated in the long-run. While long-run parameters estimated posit a significantly positive relationship between financial performance and liquidity, causality test does not indicate any direction of causality between the series.

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)0.004
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.206
Teacher spread0.192 · 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

Citations51
Published2016
Admission routes1
Has abstractyes

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