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`

.

# NOT RUN { 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")) # }