Plot Financial Charts in ggplot2

Financial charts provide visual cues to open, high, low, and close prices. Use coord_x_date() to zoom into specific plot regions. The following financial chart geoms are available:

• Bar Chart

• Candlestick Chart

Usage

geom_barchart(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  colour_up = "darkblue",
  colour_down = "red",
  fill_up = "darkblue",
  fill_down = "red",
  ...
)

geom_candlestick(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  colour_up = "darkblue",
  colour_down = "red",
  fill_up = "darkblue",
  fill_down = "red",
  ...
)

Arguments

mapping

Set of aesthetic mappings created by ggplot2::aes() or ggplot2::aes_(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot2::ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See ggplot2::fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame., and will be used as the layer data.

stat

The statistical transformation to use on the data for this layer, either as a ggproto Geom subclass or as a string naming the stat stripped of the stat_ prefix (e.g. "count" rather than "stat_count")

position

Position adjustment, either as a string naming the adjustment (e.g. "jitter" to use position_jitter), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.

na.rm

If TRUE, silently removes NA values, which typically desired for moving averages.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behavior from the default plot specification, e.g. ggplot2::borders().

colour_up, colour_down

Select colors to be applied based on price movement from open to close. If close >= open, colour_up is used. Otherwise, colour_down is used. The default is "darkblue" and "red", respectively.

fill_up, fill_down

Select fills to be applied based on price movement from open to close. If close >= open, fill_up is used. Otherwise, fill_down is used. The default is "darkblue" and "red", respectively. Only affects geom_candlestick().

...

Other arguments passed on to ggplot2::layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like color = "red" or size = 3. They may also be parameters to the paired geom/stat.

Aesthetics

The following aesthetics are understood (required are in bold):

• x, Typically a date

• open, Required to be the open price

• high, Required to be the high price

• low, Required to be the low price

• close, Required to be the close price

• alpha

• group

• linetype

• size

See also

See individual modeling functions for underlying parameters:

• geom_ma() for adding moving averages to ggplots

• geom_bbands() for adding Bollinger Bands to ggplots

• coord_x_date() for zooming into specific regions of a plot

Examples

library(dplyr)
library(ggplot2)
library(lubridate)

AAPL <- tq_get("AAPL", from = "2013-01-01", to = "2016-12-31")

# Bar Chart
AAPL %>%
    ggplot(aes(x = date, y = close)) +
    geom_barchart(aes(open = open, high = high, low = low, close = close)) +
    geom_ma(color = "darkgreen") +
    coord_x_date(xlim = c("2016-01-01", "2016-12-31"),
                 ylim = c(20, 30))


# Candlestick Chart
AAPL %>%
    ggplot(aes(x = date, y = close)) +
    geom_candlestick(aes(open = open, high = high, low = low, close = close)) +
    geom_ma(color = "darkgreen") +
    coord_x_date(xlim = c("2016-01-01", "2016-12-31"),
                 ylim = c(20, 30))