This paper reviews the recent developments in the field of the variance-ratio tests of random walk and martingale hypothesis. In particular, we present the conventional individual and multiple VR tests as well as their improved modifications based on power-transformed statistics, rank and sign tests, subsampling and bootstrap methods, among others. We also re-examine the weak-form efficiency for five emerging equity markets in Latin America.

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A Monte Carlo experiment is conducted to compare power properties of alternative tests for the martingale difference hypothesis. Overall, we find that the wild bootstrap automatic variance ratio test shows the highest power against linear dependence; while the generalized spectral test performs most desirably under nonlinear dependence.