R: Plot Bollinger Bands using Moving Averages

geom_bbands {tidyquant}

R Documentation

Plot Bollinger Bands using Moving Averages

Description

Bollinger Bands plot a range around a moving average typically two standard deviations up and down. The geom_bbands() function enables plotting Bollinger Bands quickly using various moving average functions. The moving average functions used are specified in TTR::SMA() from the TTR package. Use coord_x_date() to zoom into specific plot regions. The following moving averages are available:

Simple moving averages (SMA): Rolling mean over a period defined by n.
Exponential moving averages (EMA): Includes exponentially-weighted mean that gives more weight to recent observations. Uses wilder and ratio args.
Weighted moving averages (WMA): Uses a set of weights, wts, to weight observations in the moving average.
Double exponential moving averages (DEMA): Uses v volume factor, wilder and ratio args.
Zero-lag exponential moving averages (ZLEMA): Uses wilder and ratio args.
Volume-weighted moving averages (VWMA): Requires volume aesthetic.
Elastic, volume-weighted moving averages (EVWMA): Requires volume aesthetic.

Usage

geom_bbands(
  mapping = NULL,
  data = NULL,
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  ma_fun = SMA,
  n = 20,
  sd = 2,
  wilder = FALSE,
  ratio = NULL,
  v = 1,
  wts = 1:n,
  color_ma = "darkblue",
  color_bands = "red",
  alpha = 0.15,
  fill = "grey20",
  ...
)

geom_bbands_(
  mapping = NULL,
  data = NULL,
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  ma_fun = "SMA",
  n = 10,
  sd = 2,
  wilder = FALSE,
  ratio = NULL,
  v = 1,
  wts = 1:n,
  color_ma = "darkblue",
  color_bands = "red",
  alpha = 0.15,
  fill = "grey20",
  ...
)

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.
`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 behaviour from the default plot specification, e.g. `ggplot2::borders()`.
`ma_fun`	The function used to calculate the moving average. Seven options are available including: SMA, EMA, WMA, DEMA, ZLEMA, VWMA, and EVWMA. The default is `SMA`. See `TTR::SMA()` for underlying functions.
`n`	Number of periods to average over. Must be between 1 and `nrow(x)`, inclusive.
`sd`	The number of standard deviations to use.
`wilder`	logical; if `TRUE`, a Welles Wilder type EMA will be calculated; see notes.
`ratio`	A smoothing/decay ratio. `ratio` overrides `wilder` in `EMA`, and provides additional smoothing in `VMA`.
`v`	The 'volume factor' (a number in [0,1]). See Notes.
`wts`	Vector of weights. Length of `wts` vector must equal the length of `x`, or `n` (the default).
`color_ma`, `color_bands`	Select the line color to be applied for the moving average line and the Bollinger band line.
`alpha`	Used to adjust the alpha transparency for the BBand ribbon.
`fill`	Used to adjust the fill color for the BBand ribbon.
`...`	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
high, Required to be the high price
low, Required to be the low price
close, Required to be the close price
volume, Required for VWMA and EVWMA
colour, Affects line colors
fill, Affects ribbon fill color
alpha, Affects ribbon alpha value
group
linetype
size

Examples

# Load libraries
library(tidyquant)
library(dplyr)
library(ggplot2)


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

# SMA
AAPL %>%
    ggplot(aes(x = date, y = close)) +
    geom_line() +           # Plot stock price
    geom_bbands(aes(high = high, low = low, close = close), ma_fun = SMA, n = 50) +
    coord_x_date(xlim = c(as_date("2016-12-31") - dyears(1), as_date("2016-12-31")),
                 ylim = c(75, 125))


# EMA
AAPL %>%
   ggplot(aes(x = date, y = close)) +
   geom_line() +           # Plot stock price
   geom_bbands(aes(high = high, low = low, close = close),
                  ma_fun = EMA, wilder = TRUE, ratio = NULL, n = 50) +
   coord_x_date(xlim = c(as_date("2016-12-31") - dyears(1), as_date("2016-12-31")),
                ylim = c(75, 125))


# VWMA
AAPL %>%
    ggplot(aes(x = date, y = close)) +
    geom_line() +           # Plot stock price
    geom_bbands(aes(high = high, low = low, close = close, volume = volume),
                   ma_fun = VWMA, n = 50) +
    coord_x_date(xlim = c(as_date("2016-12-31") - dyears(1), as_date("2016-12-31")),
                ylim = c(75, 125))