Macroeconomic factors and emerging equity market: A contextual analysis using quantile regression

Mousumi Bhattacharya ORCID logo, Sharad Nath Bhattacharya ORCID logo

https://doi.org/10.22495/cgsrv6i1p3

Abstract

This article examines the role of macroeconomic factors in influencing Indian stock market movements across different market conditions. The study is important for market participants and policymakers as macroeconomic factors may be the source of systematic risk that influences the stock market. We employ factor analysis as a solution to the multicollinearity issues associated with multiple macroeconomic factors. Using three statistical factors built from macroeconomic factors, we show how they impact the stock market, particularly during up and down market conditions. While the influence of foreign exchange rate, broad money supply, economic growth, wholesale inflation, global equity markets, and export is positive and stable across market conditions, an inverse relationship between contemporaneous bond yield and equity market movements is evidenced. Gold and foreign institutional investment inflows seem to exert an increasingly negative influence on market movements at extreme up-market conditions. These findings call for active intervention by policymakers to stabilise the market during extreme market conditions.

Keywords: Macroeconomic Factors, Stock Market, Factor Analysis, Quantile Regression

Authors’ individual contribution: Conceptualization — S.N.B.; Methodology — M.B. and S.N.B.; Software — M.B.; Validation — M.B.; Formal Analysis — M.B. and S.N.B.; Investigation — M.B.; Resources — M.B.; Writing — Original Draft — M.B.; Writing — Review & Editing — S.N.B.

Declaration of conflicting interests: The Authors declare that there is no conflict of interest.

JEL Classification: C22, E44, G12

Received: 19.01.2021
Accepted: 18.02.2022
Published online: 22.02.2022

How to cite this paper: Bhattacharya, M., & Bhattacharya, S. N. (2022). Macroeconomic factors and emerging equity market: A contextual analysis using quantile regression. Corporate Governance and Sustainability Review, 6(1), 22–31. https://doi.org/10.22495/cgsrv6i1p3



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