Before revision:  Unfortunately, even testing the significance of simple dependence measures, such as Pearson correlation, is complicated by altered sampling properties when autocorrelation is present in the individual time series .
After revision:  Unfortunately, the hypothesis tests that are used to determine statistically significant directed or multivariate relationships from time-series data often yield spurious associations (Type I errors) or omit causal relationships (Type II errors). This is due to the autocorrelation present in the individual time series .