Metrics for same signal
It is better to formulate this problem in terms of classification, not regression. For example, you can apply sign transformation on your labels (e.g. $y = numpy.sign(y)$) before training the model, then fit the model with classification loss (like binary cross-entropy), and then you can use accuracy for measuring the performance. Using accuracy with regression setup outputs zero because comparing real numbers usually outputs False (like 1.2 != 1.19).