Plots the efficient frontier of an optimized portfolio and allows to add points and lines from specif portfolios
frontierPlot(object, frontier = c("both", "lower", "upper"),
col = c("black", "grey"), add = FALSE, labels = TRUE,
return = c("mean", "mu"), risk = c("Cov", "Sigma", "CVaR", "VaR"),
auto = TRUE, title = TRUE, ...) minvariancePoints(object, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
cmlPoints(object, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
cmlLines(object, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
tangencyPoints(object, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
tangencyLines(object, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
equalWeightsPoints(object, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
singleAssetPoints(object, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
twoAssetsLines(object, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
sharpeRatioLines(object, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
monteCarloPoints(object, mcSteps = 5000, return = c("mean", "mu"),
risk = c("Cov", "Sigma", "CVaR", "VaR"), auto = TRUE, ...)
tailoredFrontierPlot(object,
return = c("mean", "mu"), risk = c("Cov", "Sigma", "CVaR", "VaR"),
mText = NULL, col = NULL, xlim = NULL, ylim = NULL,
twoAssets = FALSE, sharpeRatio = TRUE, title = TRUE, ...)
an S4 object of class fPORTFOLIO, containing slots call, data,
specification, constraints, portfolio, title, description.
a character string, determining which part of the frontier should be
extracted. "both" stands for the full hyperbola, "lower"
for all points below the minimum variance return and "upper"
for the actual efficient frontier, by default "both".
a character string vector, setting the color. For frontierPlot
it is a two dimensional a vector; first entry is the upper part of the
frontier,
second entry the lower, by default "black" and "grey".
For the other functions the argument defines the color representation,
by default sets the default color is the rainbow palette.
a logical value, determining whether the frontier should be added to an existing plot, by default FALSE.
a character string denoting which type of return should be
plotted. Allowed values for the
return are either "mean", or "mu".
a character string denoting which type of risk should be
plotted. Allowed values for the
risk measure are either "cov", "sigma",
"VaR", or "CVaR".
a logical flag denoting if the type of return and risk to be plotted should be selected automatically, by default TRUE.
a logical flag, should the plot be automatically labeled and
decorated? By default TRUE.
a logical flag, should the plot obtain a default main title and
x- and y-labels? By default TRUE.
an integer value, the number of Monte Carlo steps.
two numeric vectors with two elelemts , the plot range. If set to NULL the values for the plot ranges are determined automatically.
a character string, representing a marginal text string. If set to NULL the value is taken from the title of the input frontier argument.
a logical flag, if TRUE, then the two assets frontier lines will be drawn.
a logical flag, if TRUE, then the Sharpe ratio will be added to the plot.
optional arguments to be passed.
frontierPlot | Plots efficient frontier, |
minvariancePoints | Adds minimum variance point, |
cmlPoints | Adds market portfolio, |
cmlLines | Adds capital market Line, |
tangencyPoints | Adds tangency portfolio point, |
tangencyLines | Adds tangency line, |
equalWeightsPoints | Adds point of equal weights portfolio, |
singleAssetPoints | Adds points of single asset portfolios, |
twoAssetsLines | Adds EF for all combinations of two assets, |
sharpeRatioLines | Adds Sharpe ratio line, |
monteCarloPoints | Adds randomly produced feasible portfolios, |
tailoredFrontierPlot | an example for a tailored plot. |
Wuertz, D., Chalabi, Y., Chen W., Ellis A. (2009); Portfolio Optimization with R/Rmetrics, Rmetrics eBook, Rmetrics Association and Finance Online, Zurich.