R/chart.BarVaR.R, R/charts.BarVaR.R
chart.BarVaR.RdPlots the periodic returns as a bar chart overlayed with a risk metric calculation.
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")
)an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns
periods specified for rolling-period calculations. Note that VaR, ES, and Std Dev with width=0 are calculated from the start of the timeseries
numeric number of periods from start of series to use to train risk calculation
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
confidence level for VaR or ModifiedVaR calculation,
default is .99
the method to use to clean outliers from return data prior to
risk metric estimation. See Return.clean and VaR
for more detail
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
if TRUE and a method for 'clean' is specified, overlays
the actual data with the "cleaned" data. See Return.clean for
more detail
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
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".
if TRUE, show the final (out of sample) value
if TRUE, show the per-period returns using green and red bars for positive and negative returns
legend location, such as in chart.TimeSeries
set the y-axis limit, same as in plot
set the line width, same as in plot
color palette to use, such as in
chart.TimeSeries
set the line type, same as in plot
adds a numerical padding to the y-axis to keep the data away when legend.loc="bottom". See examples below.
sets the legend text size, such as in
chart.TimeSeries
Choose the engine for plotting, including "default","dygraph","ggplot","plotly" and "googleVis"
sets the title text, such as in chart.TimeSeries
sets the legend text size, such as in
chart.TimeSeries
default NULL, controls column display
one of "all", "firstonly", "alternating", or "none" to control where y axis is plotted in multipanel charts
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
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")
# \dontrun{}