Is Pakistani Equity Market Integrated to the Equity Markets of Group of Eight (G8) Countries? A n Empirical Analysis of Karachi Stock Exchange
Bibliographic record
Abstract
This study looks at the dynamic relationship between the Pakistani equity market and equity markets of Group of Eight countries (G8) which includes Canada, France, Germany, Italy, Japan, Russia, UK and USA by using weekly time series data starting from June 2004 to May 2009. Multivariate Co-integration approach by Johnson and Julius (1990) shows there exists no long-term relationship between the G8 and Pakistani equity market. Vector error correction (VECM) model suggests that 100% of the lag periods disequilibrium has been corrected in the current period. Pairwise Granger Causality test shows that there exist a unidirectional causality between the equity market of Pakistan and the markets of France, Germany, Italy, Japan and United Kingdom. Impulse response analysis and variance decomposition analysis reveal that most of the shocks in Pakistani equity market are due to its own innovation and behave like exogenous. However, the markets of France, Japan, Germany and United Kingdom are exerting a little pressure on Pakistani equity markets. Therefore, by investing in Karachi Stock Exchange (KSE) the fund manager of G8 countries especially Canada, Italy, Russia and USA is capable of getting the advantage of portfolio diversification.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".