Create returnPrediction S3 object
create_return_prediction(data, label)
Data that will be used for prediction
Column name of the actual return
returnPrediction S3 object
# Initialize the returnPrediction object
data <- tibble::tibble(
stock_id = 1:100,
date = seq.Date(Sys.Date(), by = "day", length.out = 100),
return_label = runif(100)
)
# Create the returnPrediction object
rp <- create_return_prediction(data, "return_label")
# Check the initial setup
print(rp)
#> $models
#> list()
#>
#> $predictions
#> # A tibble: 100 × 2
#> stock_id date
#> <int> <date>
#> 1 1 2024-05-22
#> 2 2 2024-05-23
#> 3 3 2024-05-24
#> 4 4 2024-05-25
#> 5 5 2024-05-26
#> 6 6 2024-05-27
#> 7 7 2024-05-28
#> 8 8 2024-05-29
#> 9 9 2024-05-30
#> 10 10 2024-05-31
#> # ℹ 90 more rows
#>
#> $actual_returns
#> # A tibble: 100 × 3
#> stock_id date actual_return
#> <int> <date> <dbl>
#> 1 1 2024-05-22 0.806
#> 2 2 2024-05-23 0.814
#> 3 3 2024-05-24 0.404
#> 4 4 2024-05-25 0.218
#> 5 5 2024-05-26 0.418
#> 6 6 2024-05-27 0.669
#> 7 7 2024-05-28 0.508
#> 8 8 2024-05-29 0.660
#> 9 9 2024-05-30 0.512
#> 10 10 2024-05-31 0.836
#> # ℹ 90 more rows
#>
#> $errors
#> # A tibble: 100 × 2
#> stock_id date
#> <int> <date>
#> 1 1 2024-05-22
#> 2 2 2024-05-23
#> 3 3 2024-05-24
#> 4 4 2024-05-25
#> 5 5 2024-05-26
#> 6 6 2024-05-27
#> 7 7 2024-05-28
#> 8 8 2024-05-29
#> 9 9 2024-05-30
#> 10 10 2024-05-31
#> # ℹ 90 more rows
#>
#> attr(,"class")
#> [1] "returnPrediction"