Verifying the Role of Dividends as a Mediator in the Impact of Cash Flows on Bank Stock Returns on the Iraq Stock Exchange: An Empirical Analysis
Bibliographic record
Abstract
This study aims to evaluate how the effect of COVID-19 and cash flows from operating, investing, and financing activities influence stock returns, with dividends acting as a mediator. Data were gathered from the quarterly financial reports of 20 banks listed on the Iraq Stock Exchange between 1 January 2015 and 31 December 2020. Panel data were analysed using ordinary least squares (OLS). Findings revealed that cash flows have a positive impact on stock returns. Additionally, cash flows from operating and investing activities enhanced dividends, while those from financing activities negatively affected them. Although relatively small, both effects were statistically significant at the 5% level. The analysis also showed that cash flows and dividends account for 51% of the variance in stock returns, indicating a positive yet minor relationship. The results demonstrated a weakly significant negative effect of COVID-19 on both the direct relationship between cash flows and stock returns and the direct relationship between dividends and stock returns. Cash flows and dividends positively influenced stock returns during the initial five years; however, the COVID-19 pandemic in 2020 inversely affected this relationship by 4%, which is a relatively minor impact. Consequently, this research suggests that banks should improve their cash flows by increasing deposits and investing cash reserves to boost profits and, in turn, increase stock returns. Moreover, dividend distributions should play a crucial role in investment strategies, as they attract investors, raise stock demand, and help stabilise the Iraq Stock Exchange.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".