Do Foreign Investment Flow and Overconfidence Influence Stock Price Movement? A Comparative Analysis before and after the COVID-19 Lockdown
Bibliographic record
Abstract
This study examined whether foreign investment flow and overconfidence can influence stock price movement among the publicly listed companies in Indonesia. Subsequently, this study determined whether there was any significant difference in the influence of foreign investment flow and overconfidence on stock price movement before and after the COVID-19 lockdown in Indonesia. This study focused on the manufacturing companies listed on the Indonesian Stock Exchange for the 2020 period of which the data were taken in a period of 10 days before and 10 days after the implementation of the COVID-19 lockdown in Indonesia. Using content analysis on secondary data, this study showed that there was a significant difference between the stock prices before and after the COVID-19 lockdown. However, this study showed that foreign investment flow and overconfidence were not the main factors influencing stock price movement before and after the lockdown. The findings indicate that there are other factors that contribute to stock price movement in Indonesia. This study contributes to the existing literature on whether foreign investment flow and overconfidence influence stock price movement in a pandemic world.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".