How to apply Stacking cross validation for time-series data?

Question

Normally stacking algorithm uses K-fold cross validation technique to predict oof validation that used for level 2 prediction.

In case of time-series data (say stock movement prediction), K-fold cross validation can't be used and time-series validation (one suggested on sklearn lib) is suitable to evaluate the model performance. In this case no prediction shall be made on first fold and no training shall be made on last fold. How do we use stacking algorithm cross validation technique for time-series data?