An Analysis of the Dynamic Linkages of Pakistani Stock Market with the World’s Leading Stock Markets
Bibliographic record
Abstract
Using the theoretical framework of International Portfolio Diversification (IPD), the study explores the long-run relationship between the Pakistan Stock Exchange (PSX) and the world's six leading stock exchanges of Canada, China, France, Japan, United Kingdom, and the United States. These markets are represented by the indices such as KSE-100 index (Pakistan), TSX (Canada), SSE Composite (China), CAC-40 Index (France), Nikkie-225 (Japan), FTSE-100 index (UK) and DJIA (US). An extended sample period of 27 years, has been studied ranging from 1991 to 2018, using daily, weekly, and monthly frequencies. This paper investigates the existence of cointegration among the markets by employing Johansen and Juselius bi-variate and multivariate co-integration techniques. The Augmented Dicky Fuller (ADF) and Phillip and Perron (P-P) test indicate that all the series are non stationary at level, whereas they are stationary at the first difference form. In addition, the results of the bi-variate co-integration test show that Pakistani market is weakly linked with the rest of the six markets. In addition, the findings of the multivariate co-integration test confirm two co-integrating equations—France and the UK stock exchanges are integrated on the daily data, while China and Canada stock exchanges are integrated on monthly data. An essential implication deduced from this result is that these markets are loosely connected with each other over the period investigated. Hence, international investors seeking to reduce risk can diversify their portfolio risk by including these markets in their pool of investment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".