chart.VaRSensitivity: show the sensitivity of Value-at-Risk or Expected Shortfall estimates

Description

Creates a chart of Value-at-Risk and/or Expected Shortfall estimates by confidence interval for multiple methods.

Usage

chart.VaRSensitivity(
  R,
  methods = c("GaussianVaR", "ModifiedVaR", "HistoricalVaR", "GaussianES", "ModifiedES",
    "HistoricalES"),
  clean = c("none", "boudt", "geltner"),
  elementcolor = "darkgray",
  reference.grid = TRUE,
  xlab = "Confidence Level",
  ylab = "Value at Risk",
  type = "l",
  lty = c(1, 2, 4),
  lwd = 1,
  colorset = (1:12),
  pch = (1:12),
  legend.loc = "bottomleft",
  cex.legend = 0.8,
  main = NULL,
  ylim = NULL,
  ...
)

Arguments

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

methods

one or more calculation methods indicated "GaussianVaR", "ModifiedVaR", "HistoricalVaR", "GaussianES", "ModifiedES", "HistoricalES". See VaR or ES for more detail.

clean

method for data cleaning through Return.clean. Current options are "none" or "boudt" or "geltner".

elementcolor

the color used to draw chart elements. The default is "darkgray"

reference.grid

if true, draws a grid aligned with the points on the x and y axes

xlab

set the x-axis label, same as in plot

ylab

set the y-axis label, same as in plot

type

set the chart type, same as in plot

lty

set the line type, same as in plot

lwd

set the line width, same as in plot

colorset

color palette to use, set by default to rational choices

pch

symbols to use, see also plot

legend.loc

places a legend into one of nine locations on the chart: bottomright, bottom, bottomleft, left, topleft, top, topright, right, or center.

cex.legend

The magnification to be used for sizing the legend relative to the current setting of 'cex'.

main

set the chart title, same as in plot

ylim

set the y-axis dimensions, same as in plot

…

any other passthru parameters

Details

This chart shows estimated VaR along a series of confidence intervals for selected calculation methods. Useful for comparing a method to the historical VaR calculation.

References

Boudt, K., Peterson, B. G., Croux, C., 2008. Estimation and Decomposition of Downside Risk for Portfolios with Non-Normal Returns. Journal of Risk, forthcoming.

Examples

Run this code

# NOT RUN {
data(managers)
chart.VaRSensitivity(managers[,1,drop=FALSE], 
		methods=c("HistoricalVaR", "ModifiedVaR", "GaussianVaR"), 
		colorset=bluefocus, lwd=2)

# }