The market efficiency of socially responsible investment in Korea
Bibliographic record
Abstract
Purpose This paper aims to analyze the market efficiency of socially responsible investment in Korea. The authors used the daily price of the Dow Jones Sustainability Index Korea between January 2006 and December 2015. Design/methodology/approach To analyze the unpredictability of the returns, the authors conducted runs tests, such as the Dickey–Fuller test, the Philip–Perron test, the variance ratio test and autocorrelation tests. These tests investigate whether the future price of socially responsible investment in Korea is dependent on its previous price. If the relationship is dependent, this will violate the theory of weak form of efficient market hypothesis which explains that the past price movements and data do not affect stock prices. Therefore, investors cannot gain any abnormal return by extrapolating the historical data. Findings The results suggest that the weak form of the efficient market hypothesis is not valid for the Dow Jones Sustainability Index Korea. This implies that the future price of the index is correlated with past prices. Hence, the future movement of socially responsible investment in Korea can be predicted and enables socially responsible investors to gain abnormal returns. Originality/value This is the first study to investigate the market efficiency of socially responsible investment in Korea.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".