Dynamics of Network of Global Stock Markets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper studies the co-movement pattern of 67 stock market indices in the past 5 years. In order to capture the complex interaction of the stock markets, we propose a network approach to analyze the interdependence of the individual stock markets. Specifically, stock markets are considered as network nodes, and the network links (weights of links) are defined by the dynamic conditional correlation between market indices. We reveal the structure dynamics of global stock market integration by examining the variation of the network parameters as time elapses. We show that global stock markets have time-varying synchronization, and that developed markets tend to demonstrate stronger integration while emerging markets are statistically independent of each other. Furthermore, we show that stock markets of different countries generally behave in a synchronous manner when they experience fluctuation. This volatility spillover or financial contagion phenomenon is especially notable in the frontier markets. Our work exposes the interdependence of stock markets in the world and proposes a network approach to identifying some salient global behavior of the interconnecting markets.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it