A Canonical Analysis on the Relationship between Banking Sector and Stock Market Development in Bangladesh
Bibliographic record
Abstract
This study examines the structural dependency between the developments of banking sector and stock market of Bangladesh using canonical correlation analysis. The main objective is to check whether the developments of these two financial sectors independently behave in the economic activities of Bangladesh using monthly data from 2006 to 2015. The development of banking sector is measured by a set of four indicators or variables, private sector credit, total number of branches of scheduled banks, interest rate spread and non-performing loan. Similarly another set of indicators, stock market capitalization, number of listed companies, turnover ratio and stock price volatility are used to explain the development of stock market. The multivariate time series of the two set of indicators are ensured first to be the stationary one. Then the canonical correlation analysis between the two set of indicators show that private sector credit, total No. of branches of scheduled banks are the first set of variables contribute more to construct the first canonical variate of banking sector. Market capitalization and number of listed companies are the second set of variables contribute more to construct the first canonical variate of stock market development. Finally, the correlation between the first pair of canonical variates is 0.293. Since the correlation is positive but not significant, banking and stock market developments do not significantly complement each other. Thus it is concluded that the developments of the two financial systems have been independently running during the period in financing economic activities of Bangladesh from 2006 to 2015.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".