Reactions of Large, Mid, and Small Stocks to Macroeconomic and Non-Macroeconomic Factors : Similar or Different?
DOI:
https://doi.org/10.17010/ijf/2024/v18i4/173727Keywords:
Macroeconomic
, Non-Macroeconomic, Large-Cap, Mid-Cap, Small-Cap, Stock Returns, Quantile Regression, India.JEL Classification Codes
, C31, G11, G12Paper Submission Date
, October 15, 2023, Paper sent back for Revision, February 10, 2024, Paper Acceptance Date, February 20, Paper Published Online, April 15, 2024Abstract
Purpose : This paper investigated how the stock returns of large, mid, and small companies reacted to macroeconomic and non-macroeconomic factors in India.
Methodology : We used the quantile regression method and the quarterly data between Q1 2010 – Q4 2022 for the analysis. As dependent variables, we took into account companies listed under the Large Cap100, Mid Cap100, and Small Cap100 Indian stock exchange indices. In addition, we have included inflation, interest rates, and exchange rates as macroeconomic factors. We also added non-macroeconomic indicators as proxied by the Nifty, GPR, VIX, and EPU in addition to macroeconomic variables.
Findings : It was discovered that the stock returns of small companies are negatively impacted by inflation, while huge companies see no effect at all. Furthermore, whereas small businesses are unaffected by interest rates, large and midsized businesses benefit from them. Furthermore, the Nifty, volatility, and the uncertainty surrounding economic policy benefit each of the three categories of businesses. Geopolitical risk and exchange rates also have a detrimental impact on large, mid, and small businesses.
Practical Implications : Our findings will help investors and portfolio managers recognize market patterns, control portfolio risk, foresee future shifts in the stock market, and modify their investment strategy for investments in big, mid-sized, and small businesses.
Originality : As far as we are aware, this is the first effort to investigate the impact of macro and non-macroeconomic factors on LMS companies in India using the panel quantile regression methodology.
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