EXPLORING RELATIONSHIP BETWEEN NIFTY, DJIA, AND SSE INDICES WITH CO-INTEGRATION AND GRANGER CAUSALITY

Authors

  • Dr. Pankaj Sharma Shri K. K. Shastri Government Commerce College
  • Mr. Saurabh Jain Khyati School of Business Administration

DOI:

https://doi.org/10.55955/410001

Keywords:

Relationship, Causality, Co-integration, Nifty, Dow Jones Industrial Average, SSE Composite

Abstract

The global financial share market indices play a crucial role in the interconnected and dynamic landscape of international finance and considered as barometers of overall market health. The investors rely on these markets to gauge market sentiment, make informed investment decisions, and diversify portfolios. This study uses to explore the relationship between Nifty, DJIA, and SSE through econometric analysis. The data has been collected for a period of sixteen years for comprehensive investigation. The Yahoo Finance database served as the source of the collected data. The study uses EViews Software for application the Johansen Co-integration test, to evaluate if a long-term equilibrium connection exists between the indexes. To further examine the direction and intensity of the causal association between Nifty, DJIA, and SSE, the Granger Causality test is used. The results indicate that past values of Nifty contain valuable information for predicting future values of DJIA and SSE.

References

Ali, F., Suri, P., Kaur, T., & Bisht, D. (2023). Cointegration and causality relationship of Indian stock market with selected world markets. F1000Research, 11, 1241. DOI: https://doi.org/10.12688/f1000research.123849.3

Al-Najjar, D. (2022). The Co-movement between international and emerging stock markets using ANN and stepwise models: Evidence from selected indices. Complexity, 2022, 1-14. DOI: https://doi.org/10.1155/2022/7103553

Blahun, I., & Blahun, I. (2020). The Relationship Between World and Local Stock Indices. Montenegrin journal of economics, doi: 10.14254/1800-5845/2020.16-1.4 DOI: https://doi.org/10.14254/1800-5845/2020.16-1.4

Devi, B. U., Sundar, D., & Alli, P. (2013). An effective time series analysis for stock trend prediction using ARIMA model for nifty midcap-50. International Journal of Data Mining & Knowledge Management Process, 3(1), 65. DOI: https://doi.org/10.5121/ijdkp.2013.3106

Fučík, V. (2018). Relationships between world stock market indices: evidence from economic networks. In The Impact of Globalization on International Finance and Accounting: 18th Annual Conference on Finance and Accounting (ACFA) (pp. 43-51). Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-68762-9_5

Idrees, S. M., Alam, M. A., & Agarwal, P. (2019). A prediction approach for stock market volatility based on time series data. IEEE Access, 7, 17287-17298. DOI: https://doi.org/10.1109/ACCESS.2019.2895252

Kumar, D. A., & Murugan, S. (2013, February). Performance analysis of Indian stock market index using neural network time series model. In 2013 international conference on pattern recognition, informatics and mobile engineering (pp. 72-78). IEEE. DOI: https://doi.org/10.1109/ICPRIME.2013.6496450

Kumar, R. (2011). Determinants of FIIs in India: Evidence from Granger causality test. South Asian Journal of Marketing & Management Research, 1(1), 61-68.

Lairellakpam, G., & Dash, M. (2012). A study of Granger causality of macroeconomic factors on Indian stock markets. Available at SSRN 1988811. DOI: https://doi.org/10.2139/ssrn.1988811

Lalwani, A., & Dhaddha, R. (2021). Correlation between Indian and International Stock Markets: An Empirical Study.

Marjanović, M., Mihailovic, I., & Dimitrijević, O. (2021). Međuzavisnot berzanskih indeksa sa vodećih tržišta kapitala: SAD, Nemačka i Japan. BizInfo (Blace) Journal of Economics, Management and Informatics, 12(1), 15-28. DOI: https://doi.org/10.5937/bizinfo2101015M

Mayur, M. (2017). Relationship between global stock exchanges and Indian stock market. Asian Journal of Empirical Research, 7(2), 28-41. DOI: https://doi.org/10.18488/journal.1007/2017.7.2/1007.2.28.41

Mukherjee, K., & Mishra, R. K. (2007). International stock market integration and its economic determinants: A study of Indian and world equity markets. Vikalpa, 32(4), 29-44. DOI: https://doi.org/10.1177/0256090920070403

Nair, MK. (2017). A study of relationship between indian and asian stock markets using machine learning techniques. Journal of emerging technologies and innovative research.

Ray, S. (2012). Testing granger causal relationship between macroeconomic variables and stock price behaviour: evidence from India. Advances in Applied Economics and Finance, 3(1), 470-481.

https://www.winvesta.in/blog/benefits-and-risk-of-global-investing#:~:text=Global%20investing%20enables%20you%20to,access%20by%20investing%20in%20India.

https://www.icicidirect.com/ilearn/stocks/articles/reasons-to-invest-in-global-market

https://www.investopedia.com/terms/s/stockmarket.asp

https://www.investopedia.com/articles/investing/100814/wall-streets-enduring-impact-economy.asp

https://www.sciencedirect.com/topics/economics-econometrics-and-finance/granger-causality-test#:~:text=The%20Granger-causality%20test%20was,short%20and%20the%20long%20run.

https://www.jstor.org/stable/25773607

https://stats.stackexchange.com/questions/317585/granger-causality-and-cointegration

https://royalsocietypublishing.org/doi/10.1098/rsos.172092

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Published

23-01-2025

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Articles

How to Cite

Sharma, P., & Jain, S. (2025). EXPLORING RELATIONSHIP BETWEEN NIFTY, DJIA, AND SSE INDICES WITH CO-INTEGRATION AND GRANGER CAUSALITY. Sachetas, 4(1), 1-10. https://doi.org/10.55955/410001

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