It's standard practice to validate forecasts on non-randomized test/validation splits of the same time series, since this simulates the conditions where the mod

It's standard practice to validate forecasts on non-randomized test/validation splits of the same time series, since this simulates the conditions where the model will be deployed in reality: It will know everything there is to know about the past, and it will know nothing about the future. See Hyndman's fpp2 — https://otexts.org/fpp2/accuracy.html https://otexts.org/fpp2/accuracy.html Also, his description of rolling window validation: https://robjhyndman.com/hyndsight/rolling-forecasts/ https://robjhyndman.com/hyndsight/rolling-forecasts/