Capital Market Determinants and Market Capitalization in Nigeria
Bibliographic record
Abstract
Capital market plays a crucial role in a country’s national development and economic capacity building. However, there are economic forces that determine the success of a capital market development in every nation. This study investigates the role of these economic indicators in determining the capital market performance in Nigeria using secondary data covering a period from 1998 to 2018. These data have been sourced from the World Bank Development Indicators, International Monetary Fund and CBN Statistical Bulletin, 2018 edition. The results from the regression analysis indicate that exchange rate and inflation rate have immaterial undesirable consequence on capital market capitalization (CMC) while the interest rate exerts a weighty harmful effect on CMC. The study also provides evidence that the gross domestic product (GDP) has a substantial positive impact on CMC. The study among others suggests that the growth of the economy should be sustained in order to keep boosting the capital market. However, the economic indicators such as inflation, interest rate and exchange rate should be kept under strict control by the relevant authorities in the country.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".