TimeSeries.H.W

library(tidyverse)

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library(tidyquant)

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library(tsibble)

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library(fabletools)
library(fable)

Attaching package: 'fable'

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df_daily <- tq_get(
  x = "GOOGL", 
  get = "stock.prices", 
  from = "2004-08-19" # Google went public in August 2004
)

googl_data_monthly <- df_daily %>%
  mutate(month = yearmonth(date)) %>%
  group_by(month) %>%
  summarise(adjusted = mean(adjusted, na.rm = TRUE)) %>%
  as_tsibble(index = month)


write.csv(
  x = googl_data_monthly, 
  file = "googl_monthly_data.csv",
  row.names = FALSE
)

library(tidyverse)
library(tidyquant)
library(tsibble)


n_total <- nrow(googl_data_monthly)
n_train <- round(0.80 * n_total)

train <- googl_data_monthly[1:n_train, ]
test  <- googl_data_monthly[(n_train + 1):n_total, ]

models_googl <- model(
  .data = train,
  # ETS   = ETS(adjusted),
  Drift = RW(adjusted ~ drift()),
  NAIVE = NAIVE(adjusted),
  SNAIVE = SNAIVE(adjusted)
)


h <- nrow(test)
fc_googl <- forecast(models_googl, h = h)


autoplot(object = fc_googl, data = train) + 
  labs(
    title = "Google Stock Price Forecasts", 
    x = "Time", 
    y = "Adjusted Price"
  )

Warning: `autoplot.fbl_ts()` was deprecated in fabletools 0.6.0.
ℹ Please use `ggtime::autoplot.fbl_ts()` instead.
ℹ Graphics functions have been moved to the {ggtime} package. Please use
  `library(ggtime)` instead.