A nonparametric approach to test for predictability

•We propose a nonparametric method to test for predictability.•Linear and nonlinear DGPs are considered in Monte Carlo analysis.•Our test displays more corrected size than three existing methods.•Our test has higher power than two nonparametric causality tests.

Predictability of macroeconomic and financial variables is an important issue in economics. In this paper, we propose a nonparametric test for the predictability of the direction of price changes. The Monte Carlo simulation results show that our method displays better finite-sample property than the traditional parametric Granger causality test (Granger, 1969) and two nonparametric causality tests of Hiemstra and Jones (1994) and Diks and Panchenko (2006).