cross validation and forecast combination

[newsagent]

I am wondering if time series cross validation can be applied to forecast combination. I tried the following code and it works OK.

 google_stock <- gafa_stock |>
  filter(Symbol == "GOOG", year(Date) >= 2015) |>
  mutate(day = row_number()) |>
  update_tsibble(index = day, regular = TRUE)

google_2015 <- google_stock |> filter(year(Date) == 2015)

google_2015_tr <- google_2015 |>
  stretch_tsibble(.init = 180, .step = 1) |>
  relocate(Date, Symbol, .id)
 
fc<-google_2015_tr |>
  model(auto_arima=ARIMA(Close), arima210 = ARIMA(Close ~ pdq(1,1,0))) |>
  mutate(combination = (auto_arima + arima210) / 2) |>
 forecast(h = 8) |>
  group_by(.id) |>
  mutate(h = row_number()) |>
  ungroup() |>
  as_fable(response = "Close", distribution = Close)

fc |> forecast:: accuracy(google_2015, by = c("h", ".model"))

[robjhyndman]

Yes, a combination is treated like any other model.

[newsagent]

thank you