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Compute Breakpoints Based on Sorting Variable

Source: R/compute_breakpoints.R
compute_breakpoints.Rd

Computes breakpoints based on a specified sorting. It can optionally filter the data by exchanges or lagged size quantiles before computing the breakpoints. The function requires either the number of portfolios to be created or specific percentiles for the breakpoints, but not both. The function also optionally handles cases where the sorting variable clusters on the edges, by assigning all extreme values to the edges and attempting to compute equally populated breakpoints with the remaining values.

Usage

compute_breakpoints(
  data,
  sorting_variable,
  breakpoint_options,
  data_options = NULL
)

Arguments

data

A data frame containing the dataset for breakpoint computation.

sorting_variable

A character string specifying the column name in data to be used for determining breakpoints.

breakpoint_options

A named list of breakpoint_options() for the breakpoints. The arguments include

  • n_portfolios An optional integer specifying the number of equally sized portfolios to create. This parameter is mutually exclusive with percentiles.

  • percentiles An optional numeric vector specifying the percentiles for determining the breakpoints of the portfolios. This parameter is mutually exclusive with n_portfolios.

  • breakpoints_exchanges An optional character vector specifying exchange names to filter the data before computing breakpoints. Exchanges must be stored in a column given by data_options (defaults to exchange). If NULL, no filtering is applied.

  • smooth_bunching An optional logical parameter specifying if to attempt smoothing non-extreme portfolios if the sorting variable bunches on the extremes (TRUE), or not (FALSE, the default). In some cases, smoothing will not result in equal-sized portfolios off the edges due to multiple clusters. If sufficiently large bunching is detected, percentiles is ignored and equally-spaced portfolios are returned for these cases with a warning.

  • breakpoints_min_size_threshold An optional numeric value between 0 and 1 (exclusive). When set, stocks with market capitalization below this quantile are excluded from breakpoint computation. The quantile is computed among breakpoints_exchanges stocks if specified, otherwise among all stocks. Requires a market capitalization column in the data (column name determined by data_options).

data_options

A list of class tidyfinance_data_options (created via data_options()) specifying column name mappings. The exchange element is used to specify the exchange column, and mktcap_lag is used to specify the market capitalization. Uses data_options() default if NULL: "exchange" = "exchange" and "mktcap_lag" = "mktcap_lag".

Value

A numeric vector of breakpoints of the desired length.

Note

This function will stop and throw an error if both n_portfolios and percentiles are provided or missing simultaneously.

See also

Other portfolio functions: assign_portfolio(), breakpoint_options(), compute_long_short_returns(), compute_portfolio_returns(), data_options(), filter_options(), filter_sorting_data(), implement_portfolio_sort(), portfolio_sort_options()

Examples

set.seed(42)
data <- data.frame(
  id = 1:100,
  exchange = sample(c("NYSE", "NASDAQ"), 100, replace = TRUE),
  market_cap = 1:100
)

compute_breakpoints(data, "market_cap", breakpoint_options(n_portfolios = 5))
#> [1]   1.0  20.8  40.6  60.4  80.2 100.0
compute_breakpoints(
  data,
  "market_cap",
  breakpoint_options(
    percentiles = c(0.2, 0.4, 0.6, 0.8),
    breakpoints_exchanges = c("NYSE")
  )
 )
#> [1]  1.0 19.0 31.0 59.8 80.8 97.0