R/compound.r

In yuezhengjessica/RoboPackage:

#' Part6: Rebalancing Functions
#'
#' These functions allow you --
#' @param tests ------------
#' @keywords tests
#' @export
#' @examples
#' connect.and.query = function(query, type = "get")
#' GET.value.lookup = function(table = "scaling", col2lookup = "Scaling_Ratio", col.name = "Date", col.value)
#' GET.n.until = function(column, table, n, DATE)
#' GET.column = function(table, column)
#' GET.rt.dateRange = function(first_day, last_day, tickers = slec.tickers, table = "daily_return")
#' GET.rt = function(tickers = "SHV,SHY,IEI,AGZ,STIP,TIP", table, DATE, days.all = 504, delim = ",")
#' excludeSheet
#' applyPreference = function(features, excludeSheet, riskTolerance="Low", investmentHorizon="Short")
#' check.and.print = function(x)
#' check.dateRange = function(dataset, column = "Date")
#' check.valid.tickers = function(tickers, first_day, last_day, lookback.days)
#' as.Date.n = function(x)
#' SD.year2day = function(SD_year, is.percent = FALSE)
#' SD.day2year = function(SD_day)
#' rt.quater2year = function(rt_quater)
#' rt.year2quater = function(rt_year)
#' percent = function(x){x / 100}
#' YTM2adjust_rt = function(YTM)
#' shorten.rts = function(dataset, exclude = "Date")
#' adjusted_rt2proj_rt = function(adjusted_rt, daily_rt, DATE, days.lookBackMmt=105, days.excludeMmt=21)
#' cov.period = function(DATE, days.lookBackSD = 504, daily_rt)
#' cov.matrix2 = function(cov_period, SR)
#' opti.wets.donlp2 = function(SD_1year.max=3.5, rt_1quater.min=-3, proj_rt, cov_matrix2, stress_rt, stress_drawdown=15)
#' opti.wets = function(daily_rt, forward_rt, DATE, days.lookBackSD=504, days.lookBackMmt=105, days.excludeMmt=21, SD_1year.max=3.5, rt_1quater.min=-3,forward_rt_type = "adjusted",stress_rt, stress_drawdown)
#' portfolio.SD = function(weights, cov_matrix2)
#' portfolio.rt = function(weights, rt_)
#' global.bounds = function(SD, limit)
#' notebook.declare = function(daily_rt)
#' compound = function(notebook, thisDay, cov_period.thisDay, returns.thisDay)
#' check.if.rebalance = function(SD_thisDay, lowerBound, upperBound)



compound = function(notebook, thisDay, cov_period.thisDay, returns.thisDay){
  #' compare SD of the compounded with sd from yesterday
  # based on the continuous fraction share assumption
  returns.thisDay = returns.thisDay[,-1]
  thisRow = which(notebook$Date == thisDay)
  yesterRow = thisRow - 1
  yesterDay = notebook$Date[yesterRow] #%>% as.Date()
  # h_period = GET.rt.dateRange(yesterDay, thisDay, "daily_return") %>%
  #   select(-Date)
  h_period = daily_rts %>%
    filter(Date == thisDay | Date == yesterDay) %>%
    select(-Date)

  weight.yesterDay = notebook$weights[[yesterRow]]
  SR_thisDay = GET.value.lookup(table = "scaling",
                                col2lookup = "Scaling_Ratio",
                                col.name = "Date",
                                col.value = thisDay)
  cov2 = cov.matrix2(cov_period.thisDay, SR_thisDay)

  # quick and dirty. Copy and paste.
  ## calculation
  if(TRUE){
    cm_rate = apply(h_period+1, 2, cumprod)
    cm_rate = cm_rate[nrow(cm_rate),]
    weights.thisDay=(weight.yesterDay*cm_rate)/sum(weight.yesterDay*cm_rate)
    SD.thisDay = sqrt(weights.thisDay %*% cov2 %*% weights.thisDay) * sqrt(252)
    rt.thisDay = sum(weights.thisDay * returns.thisDay)
    actual_rt = sum(weights * notebook$returns[[thisRow]])
    cum_rt = (1 + actual_rt) * notebook$cum_rt[yesterRow]

  }
  # Save result to renew the notebook
  if(TRUE){
    notebook$weights[[thisRow]] = weights.thisDay
    notebook$SD[thisRow] = SD.thisDay
    notebook$rt[thisRow] = rt.thisDay
    notebook$cov_matrix2[[thisRow]] = cov2
    notebook$actual_rt[thisRow] = actual_rt
    notebook$cum_rt[thisRow] = cum_rt

  }
  notebook$status[thisRow] = "compound"
  return(notebook)
}