Stock market and macroeconomic variables: New evidence from India

• Published in: Financial innovation (Heidelberg) Vol. 5; no. 1; pp. 1 - 17
• Main Authors: Gopinathan, R, Durai, S. Raja Sethu
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer 11.07.2019; Springer Berlin Heidelberg; Springer Nature B.V; SpringerOpen
• Subjects: Alternating conditional expectations; Cointegration analysis; Continuous wavelet transformation; Economic models; Economics; Economics and Finance; Macroeconomics; Macroeconomics/Monetary Economics//Financial Economics; Nonlinear cointegration; Political Economy/Economic Systems; Securities markets; Stock prices; India; Stock prices; Nonlinear cointegration; Alternating conditional expectations; Continuous wavelet transformation
• ISSN: 2199-4730; 2199-4730
• DOI: 10.1186/s40854-019-0145-1

Understanding the relationship between macroeconomic variables and the stock market is important because macroeconomic variables have a systematic effect on stock market returns. This study uses monthly data from India for the period from April 1994 to July 2018 to examine the long-run relationship between the stock market and macroeconomic variables. The empirical findings suggest that standard cointegration tests fail to identify any relationship among these variables. However, a transformation that extracts the actual functional relationship between these variables using the alternating conditional expectations algorithm of (J Am Stat Assoc 80:580-598, 1985) identifies strong evidence of cointegration and indicates nonlinearity in the long-run relationship. Further, the continuous partial wavelet coherency model identifies strong coherency at a lower frequency for the transformed variables, establishing the fact that the long-run relationship between stock prices and macroeconomic variables in India is nonlinear and time-varying. This evidence has far-reaching implications for understanding the dynamic relationships between the stock market and macroeconomic variables.