chart.Histogram: histogram of returns

Description

Create a histogram of returns, with optional curve fits for density and normal. This is a wrapper function for hist, see the help for that function for additional arguments you may wish to pass in.

Usage

chart.Histogram(
  R,
  breaks = "FD",
  main = NULL,
  xlab = "Returns",
  ylab = "Frequency",
  methods = c("none", "add.density", "add.normal", "add.centered", "add.cauchy",
    "add.sst", "add.rug", "add.risk", "add.qqplot"),
  show.outliers = TRUE,
  colorset = c("lightgray", "#00008F", "#005AFF", "#23FFDC", "#ECFF13", "#FF4A00",
    "#800000"),
  border.col = "white",
  lwd = 2,
  xlim = NULL,
  ylim = NULL,
  element.color = "darkgray",
  note.lines = NULL,
  note.labels = NULL,
  note.cex = 0.7,
  note.color = "darkgray",
  probability = FALSE,
  p = 0.95,
  cex.axis = 0.8,
  cex.legend = 0.8,
  cex.lab = 1,
  cex.main = 1,
  xaxis = TRUE,
  yaxis = TRUE,
  ...
)

Arguments

R

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

breaks

one of:

a vector giving the breakpoints between histogram cells,
a single number giving the number of cells for the histogram,
a character string naming an algorithm to compute the number of cells (see ‘Details’),
a function to compute the number of cells.

For the last three the number is a suggestion only. see hist for details, default "FD"

main

set the chart title, same as in plot

xlab

set the x-axis label, same as in plot

ylab

set the y-axis label, same as in plot

methods

what to graph, one or more of:

add.density to display the density plot
add.normal to display a fitted normal distibution line over the mean
add.centered to display a fitted normal line over zero
add.rug to display a rug of the observations
add.risk to display common risk metrics
add.qqplot to display a small qqplot in the upper corner of the histogram plot

show.outliers

logical; if TRUE (the default), the histogram will show all of the data points. If FALSE, it will show only the first through the fourth quartile and will exclude outliers.

colorset

color palette to use, set by default to rational choices

border.col

color to use for the border

lwd

set the line width, same as in plot

xlim

set the x-axis limit, same as in plot

ylim

set the y-axis limits, same as in plot

element.color

provides the color for drawing chart elements, such as the box lines, axis lines, etc. Default is "darkgray"

note.lines

draws a vertical line through the value given.

note.labels

adds a text label to vertical lines specified for note.lines.

note.cex

The magnification to be used for note line labels relative to the current setting of 'cex'.

note.color

specifies the color(s) of the vertical lines drawn.

probability

logical; if TRUE, the histogram graphic is a representation of frequencies, the counts component of the result; if FALSE, probability densities, component density, are plotted (so that the histogram has a total area of one). Defaults to TRUE if and only if breaks are equidistant (and probability is not specified). see hist

p

confidence level for calculation, default p=.99

cex.axis

The magnification to be used for axis annotation relative to the current setting of 'cex', same as in plot.

cex.legend

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

cex.lab

The magnification to be used for x- and y-axis labels relative to the current setting of 'cex'.

cex.main

The magnification to be used for the main title relative to the current setting of 'cex'.

xaxis

if true, draws the x axis

yaxis

if true, draws the y axis

...

any other passthru parameters to plot

Author

Peter Carl

Details

The default for breaks is "FD". Other names for which algorithms are supplied are "Sturges" (see nclass.Sturges), "Scott", and "FD" / "Freedman-Diaconis" (with corresponding functions nclass.scott and nclass.FD). Case is ignored and partial matching is used. Alternatively, a function can be supplied which will compute the intended number of breaks as a function of R.

Examples

Run this code


    data(edhec)
    chart.Histogram(edhec[,'Equity Market Neutral',drop=FALSE])

    # version with more breaks and the 
	   # standard close fit density distribution
    chart.Histogram(edhec[,'Equity Market Neutral',drop=FALSE], 
			breaks=40, methods = c("add.density", "add.rug") )

    chart.Histogram(edhec[,'Equity Market Neutral',drop=FALSE], 
			methods = c( "add.density", "add.normal") )

    # version with just the histogram and 
    # normal distribution centered on 0
    chart.Histogram(edhec[,'Equity Market Neutral',drop=FALSE], 
			methods = c( "add.density", "add.centered") )

    # add a rug to the previous plot 
	   # for more granularity on precisely where the distribution fell
    chart.Histogram(edhec[,'Equity Market Neutral',drop=FALSE], 
			methods = c( "add.centered", "add.density", "add.rug") )

    # now show a qqplot to give us another view 
    # on how normal the data are
    chart.Histogram(edhec[,'Equity Market Neutral',drop=FALSE], 
			methods = c("add.centered","add.density","add.rug","add.qqplot"))

    # add risk measure(s) to show where those are 
	   # in relation to observed returns
    chart.Histogram(edhec[,'Equity Market Neutral',drop=FALSE], 
			methods = c("add.density","add.centered","add.rug","add.risk"))

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