What is the best metric to compute the error for complex time series data?

Question

I have a complex number time series of data of ground truth and estimated values.

I am currently using Mean square error metric to check the quality of my method: $$mse = \frac{1}{N} \sum |true-estimated|^2$$

Howver, mean square error obtains onnly 1 value.

1. Is this correct way to calculate MSE for complex data?

2.Is there any other metric to see instantenous error at every sample of complex valued time series?