Bibliographic record
Abstract
The random walk hypothesis is an important area of research in finance and many tools have been proposed to investigate the behaviour of the fluctuations in stock prices. However, a detail study on emerging Asian stock markets which employ the various unit root tests has not been done. In this paper, we employ six different unit root tests such as the Augmented Dickey and Fuller test (1979), Phillips and Perron test (1988), Kwiatkowski-Phillips-Schmidt-Shin test(1992), Dickey-Fuller GLS (ERS) test (1996), Elliot-Rothenberg-Stock Point-Optimal test (1996) and Ng and Perron (2001) unit root tests on 10 emerging Asian stock markets to detect for the presence of a random walk in stock prices. We have conducted the unit root tests during different sub-sample time periods of global financial crisis to check for robustness. To be specific, we have found that during the overall sample period (2001-2015) 8 out of 10 Asian stock markets and during the pre-crisis period (2001-2007) all the 10 Asian stock market prices do follow random walk according to the unit root tests under consideration. However, during the crisis & post-crisis period (2008-2015) we have found only 5 out of 10 Asian markets follow the random walk movement based on unit root tests.
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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 | 0.006 |
| 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 | 0.000 |
| 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".