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

R: 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

Author

Peter Carl

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


data(managers)
chart.VaRSensitivity(managers[,1,drop=FALSE], 
		methods=c("HistoricalVaR", "ModifiedVaR", "GaussianVaR"), 
		colorset=bluefocus, lwd=2)

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