R/fun_TSMOM_v2.R

In 3schwartz/SpecialeScrAndFun: Script and functions used for master thesis.

#' fun_TSMOM_v2
#'
#' @description Calculated time series momentum strategy from p. 236 and return Sharpe ratio
#'
#' @param list List of periodic data
#' @param period character vector Period of rebalance
#' @param lag int Number of lags
#' @param proAnnuVol int: Procent one scale the inverse of the volatility with
#' @param Rf double scalar or vector: Risk free rate
#' @param annu int used to annualize data
#'
#' @return A list
#'  \item{name outList}{description List with TSMOM for each crypto}
#'  \item{name Sharpe}{description Table of Sharpe ratios}
#'  \item{name Sharpe_tidy}{description Sharpe ratios given in tidy form}
#'  \item{name SharpeCum_tidy}{description Sharpe ratios cumulated given in tidy form}
#' @export
#'
fun_TSMOM_v2 <- function(list = listExcess[["months"]],
                      period = c("minutes", "hours", "days", "weeks", "months", "quarters", "years"),
                      lag = 6,
                      proAnnuVol = 0.4,
                      Rf = 0,
                      annu = 250) {

  outList <- lapply(list, function(x) {
    out <- fun_Lag_df(x, lag = lag)

    TSMOM <- as.numeric(out[-nrow(out), paste0("exReVolSign_lag", lag)]) *
      (proAnnuVol / as.numeric(out[-nrow(out), "sigma"])) *
      as.numeric(out[-1,"excessReturn"])
    out <- cbind(out, TSMOM = c(rep(NA, length(TSMOM[is.infinite(TSMOM) | is.na(TSMOM)]) + 1),
                                TSMOM[!is.infinite(TSMOM) & !is.na(TSMOM)]))
    out <-cbind(out, CumTSMOM = c(rep(NA, length(which(is.na(out[,"TSMOM"])))),
                                  cumsum(na.omit(out[,"TSMOM"]))))
  })

  SharpeList <- lapply(outList, function(x) {
      tseries::sharpe(as.numeric(x[!is.na(x[, "CumTSMOM"]), "CumTSMOM"]),
                      r = Rf, scale = sqrt(annu))
  })

  SharpeCumList <- lapply(outList, function(x) {
    x[!is.na(x[,"CumTSMOM"]),"CumTSMOM"]
  })
  SharpeCumInd <- dplyr::intersect(zoo::index(SharpeCumList[[1]]),
                                   zoo::index(SharpeCumList[[2]])) %>%
    dplyr::intersect(zoo::index(SharpeCumList[[3]])) %>%
    dplyr::intersect(zoo::index(SharpeCumList[[4]])) %>%
    lubridate::as_date()

  sharpeCum <- do.call(cbind, lapply(SharpeCumList, function(x) {
    x[SharpeCumInd]
  })) %>%
    rowSums()/length(list)
  sharpeCum <- tseries::sharpe(sharpeCum, r = Rf, scale = sqrt(annu))

  SharpeCum_tidy <- tibble::tibble(Sharpe = sharpeCum, "Freq" = paste(period), Lag = paste0(lag,"-",period))

  names(outList) <- names(list)
  names(SharpeList) <- names(list)


  Sharpe_tidy <- do.call(cbind, SharpeList) %>%
    tibble::as_tibble() %>%
    tidyr::gather(Crypto, Sharpe) %>%
    cbind(Freq = rep(period, length(SharpeList)), Lag = rep(lag, length(SharpeList)))
  Sharpe_tidy <- cbind(Sharpe_tidy[,c("Sharpe", "Freq")], Crypto = paste0(Sharpe_tidy[,"Crypto"],"-", Sharpe_tidy[,"Lag"],"-", Sharpe_tidy[,"Freq"]))

  out <- list(outList = outList,
              Sharpe = SharpeList,
              Sharpe_tidy = Sharpe_tidy,
              SharpeCum_tidy = SharpeCum_tidy)
  return(out)
}