The Lunar New Year Effect on Stock Market Returns: Evidence from Ho Chi Minh Stock Exchange
Bibliographic record
Abstract
This study is devoted to investigating the Lunar New Year effect on market returns for the Ho Chi Minh Stock Exchange (HOSE). The data employed in this study include a daily series of the VN30-Index, which is a market capitalization weighted index of 30 large capitalization and high liquidity stocks traded on the HOSE, for the period from 6 February 2012 to 31 December 2024. The empirical findings derived from ordinary least squares (OLS), exponential-generalized autoregressive conditional heteroskedasticity [EGARCH(1,1)] regression models consistently confirm that the average return in the last two days and five days before the Lunar New Year are significantly higher than the average market returns on other days of the year. However, this study finds that the average return during the first two trading days and five trading days following the Lunar New Year are not significantly different from the average market returns on other days throughout the year.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".