On economic uncertainty, stock market predictability and nonlinear spillover effects

Abstract

This paper uses a k-th order nonparametric Granger causality test to analyze whether firmlevel, economic policy and macroeconomic uncertainty indicators predict movements in real stock returns and their volatility. Linear Granger causality tests show that whilst economic policy and macroeconomic uncertainty indices can predict stock returns, firm-level uncertainty measures possess no predictability. However, given the existence of structural breaks and inherent nonlinearities in the series, we employ a nonparametric causality methodology, since the linear model is misspecified and the results emanating from it cannot be considered reliable. The nonparametric test reveals that, in fact, there is in general no predictability from the various measures of uncertainties, i.e., firm-level, macroeconomic, and economic policy uncertainty, for real stock returns. In turn, the predictability is concentrated in the volatility of real stock returns, except under the case of firm-level uncertainty. Thus, our results not only emphasize the role of economic and firm-level uncertainty measures in predicting volatility of stock returns, but also presage against using linear models which are likely to suffer from misspecification in the presence of parameter instability and nonlinear spillover effects.