An Empirical Essay to Explain the Contrarian Profits in the Tunisian Stock Market: Behavioral Approach vs. Rational Approach
Bibliographic record
Abstract
This paper aims to investigate the behavioral and the rational explanations for the contrarian profits in the Tunisian stock market. We use the CAPM and the three-factor model of Fama and French (1993, 1996) to examine the rational explanations including the market risk, the size effect and the book to market effect. Behavioral explanations include the overconfidence bias and the investor sentiment. We use the decomposition of the trading volume advanced by Chuang and Lee (2006) to extract the factor reflecting the investor overconfidence and the ARMS index to measure the investor sentiment. These two variables are included in the three-factor model of Fama and French (1993, 1996) in an attempt to confront the rational approach with the behavioral approach. The results indicate that the contrarian profits on the Tunisian stock market are explained by the market risk, the size effect and the Book to Market effect; and that once adjusted for these three risk factors, they disappear. However, only the factor reflecting overconfidence among the two behavioral factors seems to play a role in explaining these abnormal returns.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".