Construct an asset pricing factor — factorem • factorem

Given a reference dataset and a set of parameters, construct the desired asset pricing factor and returns its return and position time series by leg.

factorem(
  name = "",
  data,
  update_frequency = "month",
  return_frequency = "day",
  price_variable = "PX_LAST",
  sort_variable = "PX_LAST",
  sort_levels = T,
  weighted = T,
  ranking_period = 1L,
  long_threshold = 0.5,
  short_threshold = 0.5
)

Arguments

name	a scalar character vector specifying the name to use for the factor.
data	a dataframe/tibble. Columns must include `ticker`, `date`, `field` and `value`.
update_frequency	a scalar character vector. Specifies the rebalancing frequency. Must be one of 'year', 'semester', 'quarter', 'month', 'week' or 'day'. Defaults to 'month'.
return_frequency	a scalar character vector. Specifies the frequency of the returns output. Must be one of 'year', 'semester', 'quarter', 'month', 'week' or 'day'. Defaults to 'day'.
price_variable	a scalar character vector. Specifies the name of the variable hosting asset prices. Must be found in the `field` columns of `data`.
sort_variable	a scalar character vector. Specifies the name of the variable to use for sorting. Must be found in the `field` columns of `data`.
sort_levels	a scalar logical vector. If `TRUE`, sort is done on `sort_variable`'s levels, else on relative changes. Default: `TRUE`.
weighted	a scalar `logical` vector. If `TRUE` adjusts portoflio weights with respect to sorting variable, else equal weights are used. Defaults to `FALSE`.
ranking_period	a scalar integer vector. Specifies number of periods in term of `update_frequency` looking backward for averaging `sort_variable`. Default: 1 (sort on last observation).
long_threshold	a scalar numeric vector. Specifies the threshold for short positions. Default: 0.5.
short_threshold	a scalar numeric vector. Specifies the threshold for long positions. Default: 0.5.

Value

An S4 object of class AssetPricingFactor.