Purpose: The objective of this study was to analyze a long-term relationship between Indian stock prices and selected macroeconomic indicators. This paper investigated the long-term determinants of Indian stock prices, using monthly data from April 2005 to April 2024.

Methodology: The paper used Johansen’s cointegration and vector error correction technique to investigate the short-run dynamic linkages among Indian stock prices and key macroeconomic indicators. Further, a dynamic analysis of the determinants using impulse response function (IRF), forecast error variance decomposition (FEVD), and Granger causality was also conducted.

Findings: The empirical results showed a significant long-term relationship (cointegration) between Indian stock market performance and macroeconomic indicators like the index of industrial production, inflation, money supply, interest rate, rupee-dollar exchange rate, net exports, and global financial market performance. The signs in the cointegrating vector were consistent with the theoretical understanding of the relationship among variables. The generalized variance decompositions suggested that the level of economic activity in the domestic economy, exchange rate movements, and the global financial environment were the most important determinants of the Indian stock market.Practical

Implications: Stock markets were a crucial part of a financial economy and played a phenomenal role in the growth and development of a nation. Markets worldwide have become more open and integrated. Hence, an economy’s vulnerability to the global environment, including exogenous shocks and events, such as the 2008 global financial recession and the COVID-19 pandemic, had increased. It had become imperative to review the role of macroeconomic fundamentals in determining stock prices while accounting for such random events. The Indian stock market was sensitive to both domestic and global factors. Hence, targeting exchange rates and capital flows as policy variables was equally important as domestic fundamentals, such as economic activity.

Originality: This study included domestic and global factors as determinants of stock market prices. These findings had important policy implications as they might be crucial in the context of macroeconomic stabilization and adjustment programs.

1. Ahmed, S. (2008). Aggregate economic variables and stock markets in India. Available at SSRN. https://ssrn.com/abstract=1693544
2. Aksoy, M., Akin, f., & Zeytunlu, N. (2011). Cointegration of MENA stock markets: Turkey, Egypt and Israel. International Research Journal of Finance and Economics, 76, 47–66.
3. Asaolu, T. O., & Ogunmuyiwa, M. S. (2011). An econometric analysis of the impact of macroeconomic variables on stock market movement in Nigeria. Asian Journal of Business Management, 3(1), 72–78. https://www.airitilibrary.com/Article/Detail/20418752-201102-201508130016-201508130016-72-78
4. Chakravarty, S., & Mitra, A. (2013). Stock prices and inflation: Relationship revisited. World Journal of Modelling and Simulation, 9(3), 201–215.
5. Chen, N. - F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. The Journal of Business, 59(3), 383–403. https://www.jstor.org/stable/2352710
6. Danak, D., & Patel, N. (2020). A study of efficiency of index futures, lead-lag relationship, and speed of adjustments in India using high-frequency data. Indian Journal of Finance, 14(4), 7–23. https://doi.org/10.17010/ijf/2020/v14i4/151705
7. Dickinson, D. G. (2000). Stock market integration and macroeconomic fundamentals: An empirical analysis, 1980–95. Applied Financial Economics, 10(3), 261–276. https://doi.org/10.1080/096031000331671
8. Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. https://doi.org/10.2307/1913236
9. Errunza, V., & Hogan, K. (1998). Macroeconomic determinants of European stock market volatility. European Financial Management, 4(3), 361–377. https://doi.org/10.1111/1468-036X.00071
10. Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417. https://doi.org/10.2307/2325486
11. Fama, E. F. (1981). Stock returns, real activity, inflation, and money. The American Economic Review, 71(4), 545–565. https://www.jstor.org/stable/1806180
12. Gahlot, R. (2019). An analytical study on the effect of FIIs & DIIs on Indian stock market. Journal of Transnational Management, 24(2), 67–82. https://doi.org/10.1080/15475778.2019.1601485
13. Gay Jr., R. D. (2016). Effect of macroeconomic variables on stock market returns for four emerging economies: Brazil, Russia, India, and China. International Business & Economics Research Journal, 15(3), 119–126. https://core.ac.uk/download/pdf/268108021.pdf
14. Hiremath, G. S., & Narayan, S. (2016). Testing the adaptive market hypothesis and its determinants for the Indian stock markets. Finance Research Letters, 19, 173–180. https://doi.org/10.1016/j.frl.2016.07.009
15. Hirota, S. (2023). Money supply, opinion dispersion, and stock prices. Journal of Economic Behavior & Organization, 212, 1286–1310. https://doi.org/10.1016/j.jebo.2023.06.014
16. Jacob, T., & Raphael, R. (2019). Macroeconomic dynamics of foreign portfolio investment in India: An empirical analysis. Review of Professional Management, 17(2), 63–73. https://doi.org/10.20968/rpm/2019/v17/i2/149814
17. Johansen, S., & Juselius, K. (1990). Maximum likelihood estimation and inference on cointegration – with applications to the demand for money. Oxford Bulletin of Economics and Statistics, 52(2), 169–210. https://doi.org/10.1111/j.1468-0084.1990.mp52002003.x
18. Johansen, S., & Juselius, K. (1992). Testing structural hypotheses in a multivariate cointegration analysis of the PPP and the UIP for UK. Journal of Econometrics, 53(1–3), 211–244. https://doi.org/10.1016/0304-4076(92)90086-7
19. Karmakar, M., & Inani, S. (2019). Information share and its predictability in the Indian stock market. The Journal of Futures Markets, 39(10), 1322–1343. https://doi.org/10.1002/fut.22041
20. Kaur, H. (2004). Time varying volatility in the Indian stock markets. Vikalpa, 29(4), 25–42. https://doi.org/10.1177/0256090920040403
21. Maysami, R. C., & Koh, T. S. (2000). A vector error correction model of the Singapore stock market. International Review of Economics & Finance, 9(1), 79–96. https://doi.org/10.1016/S1059-0560(99)00042-8
22. Maysami, R. C., Wee, L. S., & Koon, K. T. (2004). Co-movement among sectoral stock market indices and cointegration among dually listed companies. Journal of Management, 23, 33–52. https://journalarticle.ukm.my/8063/1/1245-2397-1-SM.pdf
23. Meric, G., Pati, N., & Meric, I. (2011). Co-movements of the Indian stock markets with other stock markets: Implication for portfolio diversification. Indian Journal of Finance, 5(10), 13–20. https://www.indianjournaloffinance.co.in/index.php/IJF/article/view/72477
24. Mo, D., Gupta, R., Li, B., & Singh, T. (2018). The macroeconomic determinants of commodity futures volatility: Evidence from Chinese and Indian markets. Economic Modelling, 70, 543–560. https://doi.org/10.1016/j.econmod.2017.08.032
25. Modi, A. G., Patel, B., & Patel, N. (2010). The study on co-movements of selected stock markets. Available at SSRN. https://ssrn.com/abstract=2660643
26. Nagina, R. (2022). The nexus of stock markets among BRICS nations: An empirical analysis pre and post spread of the COVID-19 pandemic. Indian Journal of Finance, 16(10), 24–42. https://doi.org/10.17010/ijf/2022/v16i10/172386
27. Pal, S., & Garg, A. K. (2019). Macroeconomic surprises and stock market responses—A study on Indian stock market. Cogent Economics & Finance, 7(1), Article ID 1598248. https://doi.org/10.1080/23322039.2019.1598248
28. Pandit, B. L. (2015). Global financial crisis and the Indian stock market. In The global financial crisis and the Indian economy (pp. 91–106). Springe. https://doi.org/10.1007/978-81-322-2395-5_7
29. Radha, P., & Gopinathan, N. (2019). An empirical analysis of impact of macroeconomic variables on Indian stock market. International Journal of Recent Technology and Engineering (IJRTE), 8(3), 2033–2038. https://doi.org/10.35940/ijrte.C4528.098319
30. Rahman, M. L., & Uddin, J. (2009). Dynamic relationship between stock prices and exchange rates: Evidence from three South Asian countries. International Business Research, 2(2), 167–174.
31. Ratanapakorn, O., & Sharma, S. C. (2007). Dynamic analysis between the US stock returns and the macroeconomic variables. Applied Financial Economics, 17(5), 369–377. https://doi.org/10.1080/09603100600638944
32. Ross, S. A. (1976). The arbitrage theory of capital asset pricing. Journal of Economic Theory, 13(3), 341–360. https://doi.org/10.1016/0022-0531(76)90046-6
33. Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The Journal of Finance, 19(3), 425–442. https://doi.org/10.1111/j.1540-6261.1964.tb02865.x
34. Singh, G. (2015). The impact of macroeconomic fundamentals on stock prices revised: A study of Indian stock market. Available at SSRN. https://ssrn.com/abstract=2854749
35. Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250. https://doi.org/10.1016/0304-4076(94)01616-8
36. Tripathi, R., Singh, A. B., & Singh, P. T. (2016). Impact of key macroeconomic variables on movement of the Indian stock market with reference to BSE Sensex. Indian Journal of Finance, 10(6), 38–50. https://doi.org/10.17010/ijf/2016/v10i6/94878
37. Vohra, P. S. (2016). A study of co-movement among indices of Bombay Stock Exchange. Indian Journal of Finance, 10(9), 11–29. https://doi.org/10.17010/ijf/2016/v10i9/101476