Semi-Strong Form of Efficiency of Nigerian Stock Market: An Empirical Test in the Context of Input and Output Index
Bibliographic record
Abstract
This paper examines the semi-strong form of efficiency of the Nigerian stock market. Such examination is made in the context of whether information impounded in previous stock prices reflect current prices through the input and output index. Data for the study were from secondary sources and it spans from 2005-2013. The population for this study encompasses all the companies that traded in the period of January 1, 2005 to December 31, 2013. All these companies are ranked according to their capitalization and a random sampling technique was employed to select the companies that have the capitalization values above the average value. The study made use of modified transfer function model to estimate the market index which is represented by the outputindex and the computed selected securities represented by the input index which is tantamount to published information. Findings from the paper show that publicly published information captured by the input index commands significant effect on the stock market represented by the output index hence making the Nigerian stock market to be semi-strong inefficient.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".