Download and Process Fama-French Factor Data

Downloads and processes Fama-French factor data based on the specified dataset name and date range. The data is downloaded directly from Kenneth French's data library and processed into a structured format, including date conversion, scaling factor values, and filtering by the specified date range.

Usage

download_data_factors_ff(
  dataset = NULL,
  start_date = NULL,
  end_date = NULL,
  type = deprecated()
)

Arguments

dataset

The name of the Fama-French dataset to download (e.g., "Fama/French 3 Factors").

start_date

Optional. A character string or Date object in "YYYY-MM-DD" format specifying the start date for the data. If not provided, the full dataset is returned.

end_date

Optional. A character string or Date object in "YYYY-MM-DD" format specifying the end date for the data. If not provided, the full dataset is returned.

type

Use dataset instead.

Value

A tibble with processed factor data, including the date, risk-free rate, market excess return, and other factors, filtered by the specified date range.

Details

If there are multiple tables in the raw Fama-French data (e.g., value-weighted and equal-weighted returns), then the function only returns the first table because these are the most popular. Download the source ZIP archive directly if you need less commonly used tables.

References

Fama, E. F., & French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33(1), 3-56. doi:10.1016/0304-405X(93)90023-5

Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22. doi:10.1016/j.jfineco.2014.10.010

Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57-82. doi:10.1111/j.1540-6261.1997.tb03808.x

See also

Other download functions: download_data(), download_data_constituents(), download_data_factors_q(), download_data_fred(), download_data_fred_md(), download_data_huggingface(), download_data_jkp(), download_data_macro_predictors(), download_data_osap(), download_data_pastor_stambaugh(), download_data_risk_free(), download_data_stambaugh_yuan(), download_data_stock_prices(), download_factor_library_grid(), download_factor_library_ids()

Examples

# \donttest{
  download_data_factors_ff(
    "Fama/French 3 Factors", "2000-01-01", "2020-12-31"
  )
#> # A tibble: 252 × 5
#>    date       mkt_excess     smb     hml risk_free
#>    <date>          <dbl>   <dbl>   <dbl>     <dbl>
#>  1 2000-01-01    -0.0474  0.0512 -0.011     0.0041
#>  2 2000-02-01     0.0246  0.213  -0.0973    0.0043
#>  3 2000-03-01     0.0521 -0.174   0.0848    0.0047
#>  4 2000-04-01    -0.0639 -0.0603  0.0645    0.0046
#>  5 2000-05-01    -0.0439 -0.0607  0.0458    0.005 
#>  6 2000-06-01     0.0468  0.127  -0.0803    0.004 
#>  7 2000-07-01    -0.0248 -0.0282  0.081     0.0048
#>  8 2000-08-01     0.0703 -0.005  -0.014     0.005 
#>  9 2000-09-01    -0.0544 -0.0172  0.0722    0.0051
#> 10 2000-10-01    -0.0278 -0.0383  0.0564    0.0056
#> # ℹ 242 more rows
  download_data_factors_ff(
    "10 Industry Portfolios", "2000-01-01", "2020-12-31"
  )
#> # A tibble: 252 × 11
#>    date         nodur   durbl   manuf   enrgy   hitec   telcm   shops    hlth
#>    <date>       <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
#>  1 2000-01-01 -0.0472 -0.0133 -0.0866  0.0128 -0.0521 -0.0385 -0.110   0.0763
#>  2 2000-02-01 -0.0627 -0.0881 -0.0374 -0.056   0.180  -0.0369 -0.0395 -0.0251
#>  3 2000-03-01  0.0743  0.109   0.0752  0.119   0.0409  0.0827  0.134  -0.0003
#>  4 2000-04-01 -0.0196  0.0869  0.0146 -0.0231 -0.106  -0.0833 -0.0448  0.0504
#>  5 2000-05-01  0.071  -0.123  -0.0172  0.0939 -0.108  -0.0997 -0.0283  0.0372
#>  6 2000-06-01  0.0218 -0.0899 -0.0128 -0.0505  0.126   0.0399 -0.0221  0.110 
#>  7 2000-07-01  0.0072  0.0473 -0.0145 -0.0268 -0.0517 -0.0727 -0.0122 -0.0651
#>  8 2000-08-01 -0.0208  0.0544  0.0741  0.0875  0.127  -0.0149 -0.024   0.035 
#>  9 2000-09-01  0.0373 -0.0416 -0.057   0.0456 -0.147  -0.0445  0.0266  0.0367
#> 10 2000-10-01  0.0748  0.0255  0.034  -0.0281 -0.0747 -0.0017 -0.0175  0.0206
#> # ℹ 242 more rows
#> # ℹ 2 more variables: utils <dbl>, other <dbl>
# }