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Record W4408198723 · doi:10.3390/jrfm18030137

Navigating the Trade-Offs: The Impact of Aggressive Working Capital Policies on Stock Return Volatility

2025· article· en· W4408198723 on OpenAlexvenueno aff
Chun‐Hao Chang, Julia Chou, Krishnan Dandapani

Bibliographic record

VenueJournal of risk and financial management · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicWorking Capital and Financial Performance
Canadian institutionsnot available
Fundersnot available
KeywordsStock (firearms)Volatility (finance)EconomicsMonetary economicsBusinessInternational economicsFinancial economicsGeography

Abstract

fetched live from OpenAlex

This paper examines the relationship between a firm’s working capital policy and the volatility of its stock returns. We find that a firm with an aggressive working capital policy tends to exhibit a higher level of return volatility. This finding is robust across years and industries after controlling for factors such as financial stability and sales growth. Our results further indicate that aggressively managed working capital policy affects return volatility through idiosyncratic risk. A decrease in working capital results in the contemporaneous and subsequent increases of return volatility. Our evidence is consistent with the conjecture that there is an important link between a firm’s working capital policy and its stock return volatility. Thus, firm managers must incorporate the potential costs associated with higher stock return volatility into their working capital decision-making when adopting a tightened working capital policy.

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)0.002
metaresearch head score (Gemma)0.014
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
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.246
Teacher spread0.237 · 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
Published2025
Admission routes1
Has abstractyes

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