Tunisian corporate bond market liquidity: a qualitative approach
Bibliographic record
Abstract
Purpose This study aims to explore the failures of Tunisian secondary corporate bond market liquidity to understand the determinants of corporate bond market liquidity at large. Design/methodology/approach We adopted a qualitative approach to studying the Tunisian Stock Exchange. Dealers’ perceptions were collected through semi-structured face-to-face interviews; the data was recorded, transcribed and thematically analysed. Findings Secondary corporate bond market failures are due, in part, to microstructural choices – especially the use of an over-the-counter market as a trading venue. The absence of a corporate bond yield curve, a narrow investor base, market participants’ lack of financial education and authorities’ attitudes are equally responsible. Research limitations/implications This study is useful to researchers, policymakers and practitioners, as it identifies microstructural and other factors affecting the Tunisian secondary corporate bond market. We interviewed only Tunisian dealers while ignoring other categories of market participants. Furthermore, a focus group discussion could have improved our understanding of the determinants of the Tunisian secondary corporate bond market. Originality/value This paper aimed to qualitatively discuss several issues related to the Tunisian secondary corporate bond market. To date, little academic research has addressed this topic in the illiquid and non-transparent corporate bond markets.
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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 | 0.036 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".