Problem: I'm building a time series forecasting model for daily data wherein, the aim is to forecast for the next one week. So, to validate the model, I'm using a moving window based validation wherein, I take 8 weeks (56 days) of data and forecast for the next one week (7 days) and then I move the window by 7 days till the end of series. With the actual and forecasted values, I'm able to measure the accuracy of forecast.
Ask: Now I want to perform a benchmarking of the model with something very simple like moving average over multiple windows (30, 45, 60) day windows. Is this kind of benchmarking statistically correct ? What is the correct way to benchmark a timeseries forecasting model with something simple like moving average ?