IMIB Journal of Innovation and Management
issue front

Sitaram Pandey1

First Published 1 Dec 2022. https://doi.org/10.1177/ijim.221086678
Article Information Volume 1, Issue 1 January 2023
Corresponding Author:

Sitaram Pandey, University Department of Management, Vinoba Bhave University, NH 33, Sindoor, Hazaribagh, Jharkhand 825301, India.
Email: spandey1203@gmail.com

1 University Department of Management, Vinoba Bhave University, Hazaribagh, Jharkhand, India

This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www. creativecommons.org/licenses/by-nc/4.0/) which permits non-Commercial use, reproduction and distribution of the work without further permission provided the original work is attributed.

Abstract

The goal of this research is to look at how the Indian stock market sectoral indices respond to three macroeconomic variables: oil price (OP), gold price (GP) and exchange rate (ER) between 2016 and 2020. The data of sectoral indices were collected from the Bombay Stock Exchange. The underlying series is evaluated as non-stationary at the level, but stationary in the first difference, using the augmented Dickey–Fuller unit root test.  The multivariate co-integration analysis and vector error correction model indicates that there are long-term links between macroeconomic variables and sectoral indices in the information technology sector. Meanwhile, the research using the vector auto regression model approach shows that there are short-run correlations between macroeconomic variables and sectoral indices, namely Basic Materials, Fast Moving Consumer Goods, Finance, Healthcare, Information Technology, Auto, Bankex, Power and Reality. The results document that OP, GP and ER simultaneously have a significant effect on sectoral indices in the Indian stock market. To stabilise the stock market post-COVID-19, the authorities are advised to put economic policies sector-wise to accelerate the economic growth and to maintain fiscal discipline. The authorities need to stabilise the aforementioned macroeconomic variables to accelerate the economic growth as the ER has a significant negative impact on all sectors.

Keywords

BSE sectoral indices, vector error correction model, vector auto regression model, macroeconomic variables

References

Bouri, E. (2015). Oil volatility shocks and the stock markets of oil-importing MENA economies: A tale from the financial crisis. Energy Economics, 51, 590–598.

Constantinos, K., Ektor, L. A., & Dimitrios, M. (2010). Oil price and stock market linkages in a small and oil dependent economy: The case of Greece. Journal of Applied Business Research (JABR), 26(4). https://doi.org/10.19030/jabr.v26i4.306

Dey, S., & Sampath, A. (2018). Dynamic linkages between gold and equity prices: Evidence from Indian financial services and information technology companies. Finance Research Letters, 25, 41–46.

Farooq, M. T., Keung, W. W., & Kazmi, A. A. (2004). Linkage between stock market prices and exchange rate: A causality analysis for Pakistan [with comments]. The Pakistan Development Review, 43(4), 639–649.

Gan, C., Lee, M., Yong, H. H. A., & Zhang, J. (2006). Macroeconomic variables and stock market interactions: New Zealand evidence. Investment Management and Financial Innovations, 3(4), 89–101.

Gaur, A., & Bansal, M. (2010). A comparative study of gold price movements in Indian and global markets. Indian Journal of Finance, 4(2), 32–37.

Hosseini, S. M., Ahmad, Z., & Lai, Y. W. (2011). The role of macroeconomic variables on stock market index in China and India. International Journal of Economics and Finance, 3(6), 233–243.

Jain, A., & Biswal, P. C. (2016). Dynamic linkages among oil price, gold price, exchange rate, and stock market in India. Resources Policy, 49, 179–185.

Kaliyamoorthy, S., & Parithi, S. (2012). Relationship of gold market and stock market: An analysis. International Journal of Business and Management Tomorrow, 2(6), 1–6.

Maysami, R. C., Howe, L. C., & Hamzah, M. A. (2004). Relationship between macroeconomic variables and stock market indices: Cointegration evidence from stock exchange of Singapore’s All-S sector indices. Jurnal Pengurusan, 24(1), 47–77.

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.

Nath, G. C., & Samanta, G. P. (2003). Relationship between exchange rate and stock prices in India: An empirical analysis. https://www.semanticscholar.org/paper/Relationship-between-Exchange-Rate-and-Stock-Prices-Nath-Samanta/6625a99b4ac5a4c4090c35d3a62d866603ac7c42

Ouma, W. N., & Muriu, P. (2014). The impact of macroeconomic variables on stock market returns in Kenya. International Journal of Business and Commerce, 3(11), 1–31.

Pan, M. S., Fok, R. C. W., & Liu, Y. A. (2007). Dynamic linkages between exchange rates and stock prices: Evidence from East Asian markets. International Review of Economics & Finance, 16(4), 503–520.

Patra, T., & Poshakwale, S. (2006). Economic variables and stock market returns: Evidence from the Athens stock exchange. Applied Financial Economics, 16(13), 993–1005.

Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking & Finance, 55, 1–8.

Sumner, S., Johnson, R., & Soenen, L. (2010). Spillover effects among gold, stocks, and bonds. Journal of Centrum Cathedra, 3(2), 106–120.

Tchatoka, F. D., Masson, V., & Parry, S. (2019). Linkages between oil price shocks and stock returns revisited. Energy Economics, 82, 42–61.

Tripathi, V., & Seth, R. (2014). Stock market performance and macroeconomic factors: The study of Indian equity market. Global Business Review, 15(2), 291–316.

Zhao, H. (2010). Dynamic relationship between exchange rate and stock price: Evidence from China. Research in International Business and Finance, 24(2), 103–112.


Make a Submission Order a Print Copy