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#' This function adds Vertical Price Objectives calculated with the
#' Bullish Breakout and Bearish Breakdown Method (BM) to an P&F Table.
#'
#' Finding the appropriate price objectives has been explained very good at
#' http://stockcharts.com/school/doku.php?id=chart_school:chart_analysis:point_and_figure_pri,
#' but this documentation is no longer available.
#' The function adds columns vpo_bm_boxnumber and vpo_bm_price to the given
#' P&F Table. vpo_bm_bonumber contains the boxnumber of the price objective,
#' while vpo_bm_price contains the real price objective.
#'
#' @param data Input data
#' @param reversal Number of boxes for reversal
#' @param boxsize Size of one box
#' @param log Use logarithmic scale
#'
xo.priceobjective.processor <- function(data,reversal,boxsize,log) {
# add new column to store vertical price objective for breakout method (BM)
data$vpo_bm_boxnumber <- rep(NA,times=nrow(data))
data$vpo_bm_price <- rep(NA,times=nrow(data))
# add new column to store vertical price objective for reversal method (RM)
data$vpo_rm_boxnumber <- rep(NA,times=nrow(data))
data$vpo_rm_price <- rep(NA,times=nrow(data))
# loop over every in set
for (i in 1:nrow(data)) {
# subset current data
# FIXME this is a bottleneck
mydata <- data[1:i,]
# determine vertical price objective with breakout method
# FIXME this is a bottleneck
vert.obj <- currentVPOBreakoutMethod(data=mydata,
reversal=reversal,
boxsize=boxsize,
log=log)
data$vpo_bm_boxnumber[i] <- vert.obj$boxnumber
data$vpo_bm_price[i] <- vert.obj$price
# determine vertical price objective with breakout method
# FIXME this is a bottleneck
vert.obj <- currentVPOReversalMethod(data=mydata,
reversal=reversal,
boxsize=boxsize,
log=log)
data$vpo_rm_boxnumber[i] <- vert.obj$boxnumber
data$vpo_rm_price[i] <- vert.obj$price
}
data
# TODO implement function
}
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