Analysis of cash holding for measuring the efficiency of cash management: A study on IT sector
Bibliographic record
Abstract
For measuring the efficiency of management of cash, cash holding is one of the most important financial decisions that the manager of the concerned organization, has to make in the organization.Basically, it is observed that the organization hold cash for future purposes is very negligible.If the organization invested cash in profitable securities then there is some flexibility but when it relates to the capital market holding cash is not advantageous.Generally two contradictory theories such as Trade-off theory and the Pecking order theory are considered for measuring the efficiency of cash management.In this study we generally observed measured the efficiency of Cash Management influenced by Cash Holding.We also measured whether cash holding of the organization is affected with the degree of financial leverage, size of the organization, investment and profitability.This study helps us to understand the influence of DFL, Investment and Size of the organization on Cash holding.Proper holding of cash in cash management can prevent the bankruptcy of any organization and also increases the efficiency of Cash or Liquidity management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".