chart.BarVaR: Periodic returns in a bar chart with risk metric overlay

Description

Plots the periodic returns as a bar chart overlayed with a risk metric calculation.

Usage

chart.BarVaR(
  R,
  width = 0,
  gap = 12,
  methods = c("none", "ModifiedVaR", "GaussianVaR", "HistoricalVaR", "StdDev",
    "ModifiedES", "GaussianES", "HistoricalES"),
  p = 0.95,
  clean = c("none", "boudt", "geltner"),
  all = FALSE,
  ...,
  show.clean = FALSE,
  show.horizontal = FALSE,
  show.symmetric = FALSE,
  show.endvalue = FALSE,
  show.greenredbars = FALSE,
  legend.loc = "bottomleft",
  ylim = NA,
  lwd = 2,
  colorset = 1:12,
  lty = c(1, 2, 4, 5, 6),
  ypad = 0,
  legend.cex = 0.8,
  plot.engine = "default"
)
charts.BarVaR(
  R,
  main = "Returns",
  cex.legend = 0.8,
  colorset = 1:12,
  ylim = NA,
  ...,
  perpanel = NULL,
  show.yaxis = c("all", "firstonly", "alternating", "none")
)

Arguments

R

an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns

width

periods specified for rolling-period calculations. Note that VaR, ES, and Std Dev with width=0 are calculated from the start of the timeseries

gap

numeric number of periods from start of series to use to train risk calculation

methods

Used to select the risk parameter of trailing width returns to use: May be any of:

none - does not add a risk line,
ModifiedVaR - uses Cornish-Fisher modified VaR,
GaussianVaR - uses traditional Value at Risk,
HistoricalVaR - calculates historical Value at Risk,
ModifiedES - uses Cornish-Fisher modified Expected Shortfall,
GaussianES - uses traditional Expected Shortfall,
HistoricalES - calculates historical Expected Shortfall,
StdDev - per-period standard deviation

p

confidence level for VaR or ModifiedVaR calculation, default is .99

clean

the method to use to clean outliers from return data prior to risk metric estimation. See Return.clean and VaR for more detail

all

if TRUE, calculates risk lines for each column given in R. If FALSE, only calculates the risk line for the first column

...

any other passthru parameters to chart.TimeSeries

show.clean

if TRUE and a method for 'clean' is specified, overlays the actual data with the "cleaned" data. See Return.clean for more detail

show.horizontal

if TRUE, shows a line across the timeseries at the value of the most recent VaR estimate, to help the reader evaluate the number of exceptions thus far

show.symmetric

if TRUE and the metric is symmetric, this will show the metric's positive values as well as negative values, such as for method "StdDev".

show.endvalue

if TRUE, show the final (out of sample) value

show.greenredbars

if TRUE, show the per-period returns using green and red bars for positive and negative returns

legend.loc

legend location, such as in chart.TimeSeries

ylim

set the y-axis limit, same as in plot

lwd

set the line width, same as in plot

colorset

color palette to use, such as in chart.TimeSeries

lty

set the line type, same as in plot

ypad

adds a numerical padding to the y-axis to keep the data away when legend.loc="bottom". See examples below.

legend.cex

sets the legend text size, such as in chart.TimeSeries

plot.engine

Choose the engine for plotting, including "default","dygraph","ggplot","plotly" and "googleVis"

main

sets the title text, such as in chart.TimeSeries

cex.legend

sets the legend text size, such as in chart.TimeSeries

perpanel

default NULL, controls column display

show.yaxis

one of "all", "firstonly", "alternating", or "none" to control where y axis is plotted in multipanel charts

Author

Peter Carl

Details

Note that StdDev and VaR are symmetric calculations, so a high and low measure will be plotted. ModifiedVaR, on the other hand, is assymetric and only a lower bound will be drawn.

Creates a plot of time on the x-axis and vertical lines for each period to indicate value on the y-axis. Overlays a line to indicate the value of a risk metric calculated at that time period.

charts.BarVaR places multile bar charts in a single graphic, with associated risk measures

Examples

Run this code

if (FALSE)  # not run on CRAN because of example time
data(managers)
# plain
chart.BarVaR(managers[,1,drop=FALSE], main="Monthly Returns")

# with risk line
chart.BarVaR(managers[,1,drop=FALSE], 
		methods="HistoricalVaR", 
		main="... with Empirical VaR from Inception")
		
# with lines for all managers in the sample
chart.BarVaR(managers[,1:6], 
		methods="GaussianVaR", 
		all=TRUE, lty=1, lwd=2, 
		colorset= c("red", rep("gray", 5)), 
		main="... with Gaussian VaR and Estimates for Peers")

# with multiple methods
chart.BarVaR(managers[,1,drop=FALSE],
		methods=c("HistoricalVaR", "ModifiedVaR", "GaussianVaR"), 
		main="... with Multiple Methods")

# cleaned up a bit
chart.BarVaR(managers[,1,drop=FALSE],
		methods=c("HistoricalVaR", "ModifiedVaR", "GaussianVaR"), 
		lwd=2, ypad=.01, 
		main="... with Padding for Bottom Legend")

# with 'cleaned' data for VaR estimates
chart.BarVaR(managers[,1,drop=FALSE],
		methods=c("HistoricalVaR", "ModifiedVaR"), 
		lwd=2, ypad=.01, clean="boudt", 
		main="... with Robust ModVaR Estimate")

# Cornish Fisher VaR estimated with cleaned data, 
# with horizontal line to show exceptions
chart.BarVaR(managers[,1,drop=FALSE],
		methods="ModifiedVaR", 
		lwd=2, ypad=.01, clean="boudt", 
		show.horizontal=TRUE, lty=2, 
		main="... with Robust ModVaR and Line for Identifying Exceptions")