How Macroeconomic variable affect the BSE PSU Index time series analysis from 2015 - 2025

The correlation results finds that the macroeconomic variables have an impact on BSE PSU Index prices. The findings point to a real connection between macroeconomic variables and BSE PSU Index prices — all seven variables returned very low p-values, so we can reasonably dismiss the idea that these relationships are just noise. FDI, GDP, steel prices, and oil prices all move in the similar direction as the index, which makes sense given how closely they track PSU company health. Exchange rate and repo rate show a weaker but still present relationship. Inflation goes the other way, which is expected — higher inflation erodes earnings and compresses valuations. Two things this analysis can't tell us: first, it only looks at linear relationships, and that's not always the full picture. Second, correlation doesn't settle the question of direction. The working assumption is that macro variables are influencing the index, but the causality could run the other way, or both could be reacting to something else entirely. Granger causality tests and regression methods would help untangle that — results are suggestive, not conclusive.

1.               Long-Run and Short-Run Relationships between BSE SENSEX and Macroeconomic Variables, n.d. 2.               Patel, S. (2012). The effect of macroeconomic determinants on the performance of the Indian stock market. NMIMS Management Review, 22, 117–127. 3.               Ray, P. (2012). Impact of macroeconomic factors on stock prices. Research Journal of Finance and Accounting, 3(4), 33–45. 4.               Ahmed, S. (2008). Aggregate economic variables and stock markets in India. International Research Journal of Finance and Economics, 14, 141–163. 5.               Vij, M., & Sharma, A. K. (2013). Macro-economic variables affecting stock market performance in India. Amity Global Business Review, 8, 115–128. 6.               Srinivasan, P. (2011). Causal nexus between gold market and stock market: A study with reference to NSE. Indian Journal of Applied Research, 3(7), 49–51. 7.               Mukherjee, T. K., & Naka, A. (1995). Dynamic relations between macroeconomic variables and the Japanese stock market: An application of a vector error correction model. Journal of Financial Research, 18(2), 223–237. https://doi.org/10.1111/j.1475-6803.1995.tb00563.x 8.               Maysami, R. C., & Koh, T. S. (2000). A vector error correction model of the Singapore stock market. International Review of Economics and Finance, 9(1), 79– 96. https://doi.org/10.1016/S1059-0560(99)00042-8 9.               Shahzad, S. J. H., Ferrer, R., Ballester, L., & Umar, Z. (2016). Risk transmission between Islamic and conventional stock markets: A return and volatility spillover analysis. International Review of Financial Analysis, 52, 9–26. 10.            Asmy, M., Rohilina, W., Hassama, A., & Fouad, M. (2010). Effects of macroeconomic variables on stock prices in Malaysia: An approach of error correction model (MPRA Paper No. 20970). University Library of Munich.