An Empirical Study about Window Dressing of Chinese Securities Investment Funds
Bibliographic record
Abstract
Window dressing behavior means that securities investment funds and other institutional investors try to use a series of measures to dress the fund investment portfolio and their own investment performance at the end of investment period,so as to cheat on the investors and seek much benefits through this irrational investment behavior.Using the data from the first quarter in 2003 to the fourth quarter in 2009,this paper employs the reversal effect of awkwardness of fund at the period end to examine whether the window dressing behavior exists in the closed-end funds,open-end fund and the sample with different turnover rate.The results show that in China generally there is no window dressing effect existing in the closed-end funds and open-end funds,but for those stocks with low turnover rate in the akwardness of fund,the window dressing behavior is significant.Our research on window dressing behavior has siginificant implications for secruties investors and securities regulatory authority.
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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 | 0.000 | 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 | 0.001 |
| 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".