The market efficiency of socially responsible investment in Korea
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
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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