The present paper tries to analyze the macroeconomic determinants of stock returns in a relative context using monthly data from 1999 to 2013 for a panel of emerging economies, India and China. Using modern panel data time series techniques, the paper tries to examine the relative impact of industrial production, inflation, interest rate and balance of trade on stock market returns. Using the superior Fully Modified Ordinary Least Square (FMOLS) method, it is found that inflation and balance of trade are the most important factors affecting the stock returns of India, China and the panel, followed by industrial production and rate of interest.

Economists and finance specialists have long studied stock markets. Some have tried explaining its determinants, while others have studied regional and international linkages, all in a bid to better explain and predict returns. The relationship between stock returns and different macroeconomic fundamentals has been analyzed following the Arbitrage Price Theory (APT) established by Ross (1976) and later extended by Connor and Korajczyk (1986). The attempt was to model expected returns as a function of various macroeconomic factors. The general conclusion of the theory is that an additional component of long-run return is required and obtained whenever a particular asset is influenced by systematic economic news and that no extra reward can be earned by bearing diversifiable risk.

However, the APT does not in itself say which factors explain returns best or even if they capture the entirety of the situation, which is more of an empirical question. It has been silent about the identity of these necessary factors in trying to determine stock market returns. After a decade, Chen et al. (1986) posited that five economic variables—industrial production, unanticipated inflation, changes in anticipated inflation, twist in the yield curve and changes in risk premium—are plausible sources of common variation among equity returns. Their cross-sectional regression-based empirical study finds that industrial production, anticipated inflation and risk premium are significant factors. Evidence for the remaining were mixed and varied with the period of investigation, importantly the New York Stock Exchange on which the testing was done despite being a weighted index could not significantly predict future time series variability of its’ own returns. A problem with the approach was that the variable selection was very subjective. Subsequent literature has tried to identify and explain a few variables which by and large explain stock market returns in a country. This practice in tune with the APT makes the residuals as small as possible, so as to minimize the unexplained or arbitrary part of the stock returns. The theory highlights the below listed variables the most: Inflation: Theory by and large gives two views on relation between inflation and stock returns. The first and earlier view draws on Fisher (1930), who stated that expected rates of return consist of a ‘real’ return plus the expected rate of inflation and the real return does not move systematically with the rate of inflation. In short, investors will on average be fully compensated for erosion in purchasing power. However, another view supported by Geske and Roll (1983) argues that a rise in expected inflation rate leads to restrictive monetary policies, which would increase the interest rates and hence have a negative effect on stock market activity. The effect of high interest rates would not be neutralized by an increase in cash flow resulting from inflation, but cash flows do not grow at the same rate as inflation. Hence, theoretically it is still a matter of debate (Fama, 1981).

Applied Economics Journal, What Determines, Stock Returns, Effects of Fiscal, Monetary, Trade Variables, Fully Modified Ordinary Least Square (FMOLS), Arbitrage Price Theory (APT), Vector Error Correction Model (VECM), including inflation.