Stock market and macroeconomic variables: new evidence from India

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.

[1]  A. Kanas.  Non-linear cointegration between stock prices and dividends , 2003 .

[2]  S. Durai,et al.  Stock prices, inflation and output: Evidence from wavelet analysis , 2009 .

[3]  C. Granger,et al.  Co-integration and error correction: representation, estimation and testing , 1987 .

[4]  Aviral Kumar Tiwari,et al.  Oil price and exchange rates: A wavelet based analysis for India , 2013 .

[5]  H. A. Bekhet,et al.  Co-integration and causality analysis between stock market prices and their determinates in Jordan , 2013 .

[6]  S. Ross,et al.  Economic Forces and the Stock Market , 1986 .

[7]  Subhash C. Sharma,et al.  Stock market and macroeconomic fundamental dynamic interactions: ASEAN-5 countries , 2002 .

[8]  Richard Roll,et al.  The Fiscal and Monetary Linkage between Stock Returns and Inflation , 1983 .

[9]  M. Binswanger.  How Do Stock Prices Respond to Fundamental Shocks? , 2004 .

[10]  A. Babajide,et al.  The effect of fiscal and monetary policies interaction on stock market performance: Evidence from Nigeria , 2018 .

[11]  Christian Pierdzioch,et al.  Changes in the international comovement of stock returns and asymmetric macroeconomic shocks , 2009 .

[12]  Bong-Soo Lee,et al.  Causal Relations Among Stock Returns, Interest Rates, Real Activity, and Inflation , 1992 .

[13]  Angelos Kanas,et al.  Nonlinearity in the stock price-dividend relation , 2005 .

[14]  Lonnie H. Hudgins,et al.  Wavelet transforms and atmopsheric turbulence. , 1993, Physical review letters.

[15]  Clive W. J. Granger,et al.  Long memory series with attractors , 2001 .

[16]  E. Fama.  Stock Returns, Expected Returns, and Real Activity , 1990 .

[17]  J. Cochrane.  Production‐Based Asset Pricing and the Link Between Stock Returns and Economic Fluctuations , 1991 .

[18]  C. Boucher.  Asymmetric adjustment of stock prices to their fundamental value and the predictability of US stock returns , 2007 .

[19]  Philip Rothman,et al.  Time Irreversibility and Business Cycle Asymmetry , 1996 .

[20]  Jack Strauss,et al.  Stock prices and domestic and international macroeconomic activity: a cointegration approach , 2000 .

[21]  J. Friedman,et al.  Estimating Optimal Transformations for Multiple Regression and Correlation. , 1985 .

[22]  D. McMillan.  Time variation in the cointegrating relationship between stock prices and economic activity , 2005 .

[23]  Jian Zhou.  Testing for Cointegration between House Prices and Economic Fundamentals , 2010 .

[24]  Dennis W. Jansen,et al.  Nonlinear Business Cycle Dynamics: Cross-Country Evidence on the Persistence of Aggregate Shocks , 1997 .

[25]  R. Meese,et al.  An Empirical Assessment of Non-Linearities in Models of Exchange Rate Determination , 1991 .

[26]  Bent Nielsen,et al.  Cointegration Analysis in the Presence of Structural Breaks in the Deterministic Trend , 2000 .

[27]  Bong‐Soo Lee,et al.  Dynamic Relations between Stock Returns and Exchange Rate Changes , 2014 .

[28]  James G. MacKinnon,et al.  Numerical Distribution Functions for Unit Root and Cointegration Tests , 1996 .

[29]  Nicholas Sarantis,et al.  Nonlinearities, cyclical behaviour and predictability in stock markets: international evidence , 2001 .

[30]  P. Phillips,et al.  Asymptotic Properties of Residual Based Tests for Cointegration , 1990 .

[31]  A. Humpe,et al.  Non-Linear Predictability of Stock Market Returns: Comparative Evidence from Japan and the US , 2015 .

[32]  Tae-Hwy Lee,et al.  Pitfalls in testing for long run relationships , 1998 .

[33]  E. Fama.  Stock Returns, Real Activity, Inflation, and Money , 1981 .

[34]  Ying-Wong Cheung,et al.  International evidence on the stock market and aggregate economic activity , 1998 .

[35]  Rati Ram,et al.  Stock Returns, Real Activity, Inflation, and Money: Comment , 1983 .

[36]  C. Granger.  Some recent development in a concept of causality , 1988 .

[37]  T. Mukherjee,et al.  DYNAMIC RELATIONS BETWEEN MACROECONOMIC VARIABLES AND THE JAPANESE STOCK MARKET: AN APPLICATION OF A VECTOR ERROR CORRECTION MODEL , 1995 .

[38]  G. Schwert,et al.  Stock Returns and Real Activity: a Century of Evidence , 1990 .

[39]  B. Falk.  Further Evidence on the Asymmetric Behavior of Economic Time Series over the Business Cycle , 1986, Journal of Political Economy.

[40]  Xiaolei Tang,et al.  Nonlinear relationship between the real exchange rate and economic fundamentals: Evidence from China and Korea , 2013 .

[41]  Blake LeBaron,et al.  A Dynamic Structural Model for Stock Return Volatility and Trading Volume , 1995 .

[42]  B. Dumas.  Dynamic Equilibrium and the Real Exchange Rate in a Spatially Separated World , 1992 .

[43]  S. Fischer,et al.  Exchange Rates and the Current Account , 1980 .

[44]  S. Johansen.  Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models , 1991 .