Bibliographic record
Abstract
We apply GARCH (p, q) and ARCH(m) model to the daily return of DSE general index (DGEN) ranging from 1st January, 2002 to 30th July 2013 for examining market volatility. Besides, we calculate year wise standard deviation of daily return of DGEN for the same period. The result of GARCH (1, 1) process and standard deviation of the daily return confirms an abnormal volatility episode from 2009 to 2012. The highest per day volatility was observed in the first half of 2011 in both investigations. The volatility rate found in GARCH (1, 1) process is 2.44% in 2011 followed by 2.00% and 1.99% in 2009 and 2012 respectively. The highest standard deviation of return is 2.99% in 2011 followed by 2.08% in 2012 authenticate the highest volatile periods of the study. We apply ARCH (m) model in 2004 and 2013 for volatility estimate due to inapplicability of GARCH (p, q) process in those market return. The results of ARCH (m) model confirm reliable estimates of market volatility, 1.10% and 1.46% respectively. This is a part of our total research work where our main focus is to detect the factors affecting market volatility and its spillover effects in emerging markets.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".