R/npv.R

In RTL: Risk Tool Library - Trading, Risk, 'Analytics' for Commodities

#' NPV
#' @description Computes NPV with discount factor interpolation.
#' This function is used for teaching NPV and NPV at Risk and needs to be customized.
#' @param init.cost Initial investment cost. `numeric`
#' @param C Periodic cash flow. `numeric`
#' @param cf.freq Cash flow frequency in year fraction e.g. quarterly = 0.25. `numeric`
#' @param TV Terminal Value. `numeric`
#' @param T2M Time to Maturity in years. `numeric`
#' @param disc.factors Data frame of discount factors using ir.df.us() function. `numeric`
#' @param BreakEven TRUE when using a flat discount rate assumption. `logical`
#' @param BE.yield Set the flat IR rate when BreakEven = TRUE. `logical`
#' @returns List of NPV and NPV Data frame. `list`
#' @export npv
#' @author Philippe Cote
#' @examples
#' npv(
#'   init.cost = -375, C = 50, cf.freq = .5, TV = 250, T2M = 2,
#'   disc.factors = RTL::usSwapCurves, BreakEven = FALSE, BE.yield = .0399
#' )$npv
#' npv(
#'   init.cost = -375, C = 50, cf.freq = .5, TV = 250, T2M = 2,
#'   disc.factors = RTL::usSwapCurves, BreakEven = FALSE, BE.yield = .0399
#' )$df
npv <- function(init.cost = -375, C = 50, cf.freq = .25, TV = 250, T2M = 2, disc.factors = us.df, BreakEven = FALSE, BE.yield = .01) {
  if (BreakEven == TRUE) {
    disc.factors$yield <- BE.yield
    disc.factors$discounts <- exp(-BE.yield * disc.factors$times)
  }
  df <- dplyr::tibble(t = seq(from = 0, to = T2M, by = cf.freq), cf = C) %>%
    dplyr::mutate(
      cf = replace(cf, t == 0, init.cost),
      cf = replace(cf, t == T2M, TV),
      df = stats::spline(x = disc.factors$times, y = disc.factors$discounts, xout = t)$y,
      pv = cf * df
    )
  x <- list(df = df, npv = sum(df$pv))
  return(x)
}