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Predict the price of a stock over time

Source: R/data.R
prophet_models.Rd

Use a Prophet model to predict the price of a stock over time. Use daily_prophet_model for daily predictions, and monthly_prophet_model for monthly predictions.

Usage

daily_prophet_model

monthly_prophet_model

Format

A tibble with 491 / 470 rows and 3 variables.

ticker

The ticker that the model was fitted on

data

The training data that the model was fitted on

fit

The fitted Prophet model object

An object of class tbl_df (inherits from tbl, data.frame) with 482 rows and 3 columns.

Details

Each model was fitted on the time series data for an individual stock.

See also

predict_price() get_lightgbm_model()

Examples

daily_prophet_model
#> # A tibble: 502 × 3
#>    ticker data               fit           
#>    <fct>  <list>             <list>        
#>  1 A      <tibble [126 × 2]> <prophet [32]>
#>  2 AAL    <tibble [126 × 2]> <prophet [32]>
#>  3 AAP    <tibble [126 × 2]> <prophet [32]>
#>  4 AAPL   <tibble [126 × 2]> <prophet [32]>
#>  5 ABBV   <tibble [126 × 2]> <prophet [32]>
#>  6 ABC    <tibble [126 × 2]> <prophet [32]>
#>  7 ABMD   <tibble [126 × 2]> <prophet [32]>
#>  8 ABT    <tibble [126 × 2]> <prophet [32]>
#>  9 ACGL   <tibble [126 × 2]> <prophet [32]>
#> 10 ACN    <tibble [126 × 2]> <prophet [32]>
#> # … with 492 more rows
monthly_prophet_model
#> # A tibble: 482 × 3
#>    ticker data               fit           
#>    <fct>  <list>             <list>        
#>  1 A      <tibble [121 × 2]> <prophet [32]>
#>  2 AAL    <tibble [121 × 2]> <prophet [32]>
#>  3 AAP    <tibble [121 × 2]> <prophet [32]>
#>  4 AAPL   <tibble [121 × 2]> <prophet [32]>
#>  5 ABC    <tibble [121 × 2]> <prophet [32]>
#>  6 ABMD   <tibble [121 × 2]> <prophet [32]>
#>  7 ABT    <tibble [121 × 2]> <prophet [32]>
#>  8 ACGL   <tibble [121 × 2]> <prophet [32]>
#>  9 ACN    <tibble [121 × 2]> <prophet [32]>
#> 10 ADBE   <tibble [121 × 2]> <prophet [32]>
#> # … with 472 more rows