Dissemination of Information on Investor Attention, Firm Size, and Year-End Market Dynamics: An Empirical Study of the Indian Stock Market
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper investigates the dissemination and presence of the “Year-End Market Surge”, commonly referred to as the “Christmas Rally”, in the Indian stock market. In developed nations, this phenomenon describes a notable increase in stock prices typically observed during the last week of December and the first two trading days of January. Recent reports in the popular press suggest that a similar trend has been witnessed in the Indian stock market over recent years. However, there remains a lack of systematic research on this subject. Therefore, this study rigorously examines whether this market surge, which poses a potential challenge to the Efficient Market Hypothesis (EMH), is observable in the Indian context. Furthermore, the paper explores the dissemination of firm-specific trading patterns to identify characteristics of companies that have consistently delivered positive returns during this period over multiple years. The findings reveal that larger stock portfolios in the Indian market consistently benefit from the Year-End Market Surge effect, delivering higher abnormal returns compared to smaller portfolios. These results provide important insights into the role of firm size in capturing the benefits of this seasonal market anomaly.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it