Stock candlestick drawing issues with geom_boxplot

Question

I am using geom_boxplot to draw candlesticks using stock market data. The problem is that the individual boxplot's upper and lower edges as well as the upper whisker end point show up way higher on the y-axis than their corresponding values. The relative height (difference between upper and lower edges) and the end point of the lower whisker of each boxplot are fine though. Here's my code :

candlestickPlot <- function(x){

library("ggplot2")

# x is a data.frame with columns 'date','open','high','low','close'
x$candleLower <- pmin(x$open, x$close)
x$candleUpper <- pmax(x$open, x$close)
x$candleMiddle <- NA
x$fill <- "red"
x$fill[x$open < x$close] = "green"

# Draw the candlesticks
g <- ggplot(x, aes(x=date, lower=candleLower, middle=candleMiddle, upper=candleUpper, ymin=low, ymax=high)) 
g <- g + geom_boxplot(stat='identity', aes(group=date, fill=fill))
g 
}

Here's x :

    date     close volume  open  high   low
5 2013-12-30 25.82 3525026 27.30 27.76  25.7
4 2013-12-31 27.41 5487204 25.25 27.70 25.25
3 2014-01-02 30.70 7835374 29.25 31.24 29.21
2 2014-01-03 30.12 4577278 31.49 31.80 30.08
1 2014-01-06 30.65 4042724 30.89 31.88 30.37

Am I doing something wrong here?

Answer 1

Could not completely understand your problem but this seems to work nicely:

http://www.perdomocore.com/2012/using-ggplot-to-make-candlestick-charts-alpha/

Answer 2

Thank you FXQuantTrader for introducing a beautiful and fast alternative approach to the candlestick bars in R! Awesome, concise, easy to read! Here comes a bit improved version of FXQuantTrader's solution, which include:
  - wraps it into a function
  - supports lower resolution (down to 1 sec bars)
  - changes candle's whiskers colour from black to proper one
  - adds small horizontal line for bars with Close == Open
  - adds 3rd colour (blue) to bars with Close == Open
  - adds 'alpha' argument which allows you to make the whole candlesticks chart more transparent, so when you draw on top some Bollinger Bands and/or Moving Averages the bars will be less distracting (more like a background)
- a bit more comments for newbies to figure out what is going on :)

Here she comes:

library(ggplot2)
library(quantmod)
draw_candles <- function(df, title_param, alpha_param = 1){
  df$change <- ifelse(df$Close > df$Open, "up", ifelse(df$Close < df$Open, "down", "flat"))

  # originally the width of the bars was calculated by FXQuantTrader with use of 'periodicity()', which 
  # seems to work ok only with: ‘minute’,‘hourly’, ‘daily’,‘weekly’, ‘monthly’,
  # ‘quarterly’, and ‘yearly’, but can not do 1 sec bars while we want arbitrary bar size support!-)
  # df$width <- as.numeric(periodicity(df)[1])
  # So let us instead find delta (seconds) between 1st and 2nd row and just 
  # use it for all other rows. We check 1st 3 rows to avoid larger "weekend gaps"
  width_candidates <- c(as.numeric(difftime(df$Date[2], df$Date[1]), units = "secs"), 
                        as.numeric(difftime(df$Date[3], df$Date[2]), units = "secs"), 
                        as.numeric(difftime(df$Date[4], df$Date[3]), units = "secs"))

  df$width_s = min(width_candidates)  # one (same) candle width (in seconds) for all the bars

  # define the vector of candle colours either by name or by rgb()
  #candle_colors = c("down" = "red", "up" = "green", "flat" = "blue")
  candle_colors = c("down" = rgb(192,0,0,alpha=255,maxColorValue=255), "up" = rgb(0,192,0,alpha=255,maxColorValue=255), "flat" = rgb(0,0,192,alpha=255,maxColorValue=255))

  # Candle chart:
  g <- ggplot(df, aes(x=Date))+
    geom_linerange(aes(ymin=Low, ymax=High, colour = change), alpha = alpha_param) +  # candle whiskerss (vertical thin lines:)
    theme_bw() +
    labs(title=title_param) +
    geom_rect(aes(xmin = Date - width_s/2 * 0.9, xmax = Date + width_s/2 * 0.9, ymin = pmin(Open, Close), ymax = pmax(Open, Close), fill = change), alpha = alpha_param) +                            # cabdke body
    guides(fill = FALSE, colour = FALSE) +
    scale_color_manual(values = candle_colors) +  # color for line
    scale_fill_manual(values = candle_colors)     # color for candle fill  

    # Handle special cases: flat bar and Open == close:
    if (any(df$change == "flat")) g <- g + geom_segment(data = df[df$change == "flat",], aes(x = Date - width_s / 2 * 0.9, y = Close, yend = Close, xend = Date + width_s / 2 * 0.9, colour = change), alpha = alpha_param)

  #print(g)
  g
}

Answer 3

There are more efficient ways to create OHLC candlesticks with ggplot2 than the way you have described using geom_boxplot. Your code seems very similar to the example in the link: http://www.perdomocore.com/2012/using-ggplot-to-make-candlestick-charts-alpha/

It seems many people are putting ggplot candlestick examples on the net that are based on the example in that link using geom_boxplot. But the problem with plotting with geom_boxplot is that the plotting itself gets slow at producing plots as the number of bars plotted increases.

Here is one computationally faster solution for plotting financial data using candlesticks/OHLC bars:

library(ggplot2)
library(quantmod)
FOSL <- getSymbols("FOSL", from="2015-01-01", auto.assign=FALSE)
names(FOSL) <- gsub("^.+\\.","",names(FOSL))  # remove "FOSL." from column names

rng <- "2015-08"
FOSL <- FOSL[rng]
FOSL <- data.frame(Date=as.POSIXct(index(FOSL)), FOSL[,1:4])

FOSL$chg <- ifelse(Cl(FOSL) > Op(FOSL), "up", "dn")
FOSL$width <- as.numeric(periodicity(FOSL)[1])
FOSL$flat_bar <- FOSL[, "High"] == FOSL[, "Low"]

# Candle chart:
pl <- ggplot(FOSL, aes(x=Date))+
  geom_linerange(aes(ymin=Low, ymax=High)) +
  theme_bw() +
  labs(title="FOSL") +
  geom_rect(aes(xmin = Date - width/2 * 0.9, xmax = Date + width/2 * 0.9, ymin = pmin(Open, Close), ymax = pmax(Open, Close), fill = chg)) + guides(fill = FALSE, colour = FALSE) + scale_fill_manual(values = c("dn" = "darkred", "up" = "darkgreen"))

# Handle special case of drawing a flat bar where OHLC = Open:
if (any(FOSL$flat_bar)) pl <- pl + geom_segment(data = FOSL[FOSL$flat_bar,], aes(x = Date - width / 2 * 0.9, y = Close, yend = Close, xend = Date + width / 2 * 0.9))

print(pl)