chart.Histogram: histogram of returns
In PerformanceAnalytics: Econometric Tools for Performance and Risk Analysis

Description Usage Arguments Details Note Author(s) See Also Examples

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.

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,
  ...
)

`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`

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.

Code inspired by a chart on:
http://zoonek2.free.fr/UNIX/48_R/03.html

Peter Carl

hist

    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"))