chart.RollingRegression {PerformanceAnalytics} | R Documentation

## A wrapper to create charts of relative regression performance through time

### Description

A wrapper to create a chart of relative regression performance through time

A group of charts in `charts.RollingRegression` displays alpha, beta, and R-squared estimates in three aligned charts in a single device.

### Usage

    chart.RollingRegression(Ra, Rb, width = 12, rf = 0, attribute = c("Beta","Alpha","R-Squared"), main = paste("Rolling ", width, "-Month ", attribute, sep = ""), xaxis = TRUE, colorset = (1:12), legend.loc = NULL, na.pad = TRUE, ...)
    charts.RollingRegression(Ra, Rb, width = 12, rf = 0, darken = FALSE, main = NULL, ...)

### Arguments

`Ra` | a vector, matrix, data frame, timeSeries or zoo object of asset returns
`Rb` | return vector of the benchmark asset
`rf` | risk free rate, in same period as your returns
`width` | number of periods to apply rolling function window over
`attribute` | one of "Beta","Alpha","R-Squared" for which attribute to show
`main` | set the chart title, same as in `plot`
`xaxis` | if true, draws the x axis
`colorset` | color palette to use, set by default to rational choices
`darken` | TRUE/FALSE whether or not to darken the color palette for better printing on some printers
`legend.loc` | places a legend into one of nine locations on the chart: bottomright, bottom, bottomleft, left, topleft, top, topright, right, or center.
`na.pad` | TRUE/FALSE If TRUE it adds any times that would not otherwise have been in the result with a value of NA. If FALSE those times are dropped.
`...` | any other passthru parameters

### Details

The atribute parameter is probably the most confusing. In mathematical terms, the different choices yeild the following:

Alpha - shows the y-intercept
Beta - shows the slope of the regression line
R-Squared - shows the degree of fit of the regression to the data

### Value

A timeseries line chart of the calculated series

### Note

Most inputs are the same as "`plot`" and are principally included so that some sensible defaults could be set.

### Author(s)

Peter Carl

### References

### See Also

`chart.RegressionDiagnostics`

### Examples

    # First we load the data
    data(edhec)
    edhec.length = dim(edhec)[1]
    start = rownames(edhec[1,])
    start
    end = rownames(edhec[edhec.length,])
    edhec.zoo = zoo(edhec, order.by = rownames(edhec))
    rf.zoo = download.RiskFree(start = start, end = end)
    sp500.zoo = download.SP500PriceReturns(start = "1996-12-31", end = end)

    # Now we have to align it as "monthly" data
    time(edhec.zoo) = as.yearmon(time(edhec.zoo))
    time(sp500.zoo) = as.yearmon(time(sp500.zoo))
    time(rf.zoo) = as.yearmon(time(rf.zoo))
    data.zoo = merge(edhec.zoo[,9,drop=FALSE],sp500.zoo)
    time(data.zoo) = as.Date(time(data.zoo),format="%b %Y")
    time(rf.zoo) = as.Date(time(rf.zoo),format="%b %Y")

    chart.RollingRegression(data.zoo[, 1, drop=FALSE], data.zoo[, 2, drop=FALSE], rf = rf.zoo)
    charts.RollingRegression(data.zoo[, 1, drop=FALSE], data.zoo[, 2, drop=FALSE], rf = rf.zoo)

[Package PerformanceAnalytics version 0.9.5 Index]