R/load_gains.R

In vandomed/stocks: Stock Market Analysis

#' Download Historical Gains
#'
#' Downloads historical gains for specified tickers from Yahoo! Finance, with
#' various options. Relies heavily on the \pkg{quantmod} package.
#'
#'
#' @param tickers Character vector of ticker symbols that Yahoo! Finance
#' recognizes, or "^CASH" for cash.
#' @param intercepts Numeric vector of values to add to daily gains for each
#' fund.
#' @param slopes Numeric vector of values to multiply daily gains for each fund
#' by. Slopes are multiplied prior to adding intercepts.
#' @param from Date or character string, e.g. \code{"2015-01-15"}.
#' @param to Date or character string, e.g. \code{"2018-12-31"}.
#' @param time.scale Character string. Choices are \code{"daily"},
#' \code{"monthly"}, and \code{"yearly"}.
#' @param preto.days Numeric value. If specified, function returns gains for
#' \code{preto.days} trading days prior to \code{to}. For example, to load the
#' most recent 50 daily gains, leave \code{to} and \code{time.scale} as the
#' defaults and set \code{preto.days = 50}.
#' @param prefrom.days Numeric value. If specified, function returns gains for
#' \code{prefrom.days} trading days prior to \code{from}. Useful when you want
#' to test a trading strategy starting on a particular date, but the strategy
#' requires data leading up to that date (e.g. trailing beta).
#' @param mutual.lifetimes Logical value for whether to start on the first day
#' and end on the last day of the funds' mutual lifetimes (within \code{from}
#' and \code{to}).
#' @param mutual.start Logical value for whether to start on the first day of
#' the funds' mutual lifetimes.
#' @param mutual.end Logical value for whether to end on the last day of the
#' funds' mutual lifetimes.
#' @param drop.anyNA Logical value for whether to drop dates on which prices are
#' missing for any of the funds.
#'
#'
#' @return Data frame with gains for each fund.
#'
#'
#' @examples
#' \dontrun{
#' # Load gains for Netflix and Amazon over their mutual lifetimes
#' gains <- load_gains(c("NFLX", "AMZN"))
#' }
#'
#'
#' @references
#' Jeffrey A. Ryan and Joshua M. Ulrich (2019). quantmod: Quantitative Financial
#' Modelling Framework. R package version 0.4-15.
#' \url{https://CRAN.R-project.org/package=quantmod}
#'
#'
#' @export
load_gains <- function(tickers,
                       intercepts = NULL,
                       slopes = NULL,
                       from = "1950-01-01",
                       to = Sys.Date(),
                       time.scale = "daily",
                       preto.days = NULL,
                       prefrom.days = NULL,
                       mutual.lifetimes = TRUE,
                       mutual.start = mutual.lifetimes,
                       mutual.end = mutual.lifetimes,
                       drop.anyNA = FALSE) {

  prices <- load_prices(
    tickers = tickers,
    intercepts = intercepts,
    slopes = slopes,
    from = from,
    to = to,
    time.scale = time.scale,
    preto.days = preto.days,
    prefrom.days = prefrom.days,
    mutual.start = mutual.start,
    mutual.end = mutual.end,
    drop.anyNA = drop.anyNA
  )
  cbind(Date = prices[-1, 1, drop = FALSE], sapply(prices[, -1, drop = FALSE], pchanges))

}