The prediction of future operating cash flows using accrual-based and cash-based accounting information: Empirical evidence from Vietnam
Bibliographic record
Abstract
This research was conducted for assessing the predictive ability of future cash flows from operating activities by using accounting earnings and cash flows information in the past. Data were collected from the firms listed on Ho Chi Minh Stock Exchange (HOSE) from 2009 to 2018, including the sample of 242 non-financial listed companies. Three statistical methods approaches were employed to address econometric issues and to improve the accuracy of the regression coefficients based on Ordinary Least Squares (OLS), Random Effects Model (REM), and Fixed Effects Model (FEM). The findings showed that earnings and cash flows and aggregated accruals had remarkable ability to forecast future cash flows and the model of operating cash flows combined with aggregated accruals had the most effective prediction ability for companies listed on Ho Chi Minh Stock Exchange.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".