Dynamic Connectedness and Volatility Spillover Effects of Indian Stock Market with International Stock Markets: An Empirical Investigation using DCC GARCH
Bibliographic record
Abstract
This study employs the DCC-GARCH model to investigate the dynamic connectedness between the Indian stock market and major global stock markets. Specifically, we examine daily log returns data of the National Stock Exchange (NSE) index and several international indices, including the United States, Australia, China, Germany, England, Japan, and Taiwan. Our analysis indicates a significant level of volatility spillover between the Indian stock market and the international stock market. Notably, we observe a significant positive spillover effect from the S&P 500 and FTSE 100 to the Indian stock market, suggesting the presence of contagion effects. Additionally, we find bidirectional spillover between the Indian stock market and the Nikkei 225 and Hang Seng, indicating a high level of interdependence between these markets. Our research contributes to the growing literature on the dynamic connectedness of stock markets and has important implications for policymakers and investors in emerging economies such as India. Overall, this study provides valuable insights into the nature and extent of spillover effects between the Indian and international stock markets.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".