plot.FundamentalFactorModel: plot FundamentalFactorModel object.
In R-Finance/FactorAnalytics: factor analysis

Description Usage Arguments Author(s) Examples

Generic function of plot method for fitFundamentalFactorModel.

  ## S3 method for class 'FundamentalFactorModel'
 plot(x,
    which.plot = c("none", "1L", "2L", "3L", "4L", "5L", "6L"),
    max.show = 4, plot.single = FALSE, asset.name,
    which.plot.single = c("none", "1L", "2L", "3L", "4L", "5L", "6L", "7L", "8L", "9L"),
    legend.txt = TRUE, VaR.method = "historical", ...)

`x`	fit object created by fitFundamentalFactorModel.
`which.plot`	integer indicating which plot to create: "none" will create a menu to choose. Defualt is none. 1 = "Factor returns", 2 = "Residual plots", 3 = "Variance of Residuals", 4 = "Factor Model Correlation", 5 = "Factor Contributions to SD", 6 = "Factor Contributions to ES", 7 = "Factor Contributions to VaR"
`max.show`	Maximum assets to plot. Default is 4.
`plot.single`	Plot a single asset of lm class. Defualt is FALSE.
`asset.name`	Name of the asset to be plotted.
`which.plot.single`	integer indicating which plot to create: "none" will create a menu to choose. Defualt is none. 1 = time series plot of actual and fitted values, 2 = time series plot of residuals with standard error bands, 3 = time series plot of squared residuals, 4 = time series plot of absolute residuals, 5 = SACF and PACF of residuals, 6 = SACF and PACF of squared residuals, 7 = SACF and PACF of absolute residuals, 8 = histogram of residuals with normal curve overlayed, 9 = normal qq-plot of residuals.
`legend.txt`	Logical. TRUE will plot legend on barplot. Defualt is `TRUE`.
`VaR.method`	character, method for computing VaR. Valid choices are one of "modified","gaussian","historical", "kernel". Computation is done with the `VaR` in the PerformanceAnalytics package. Default is "historical".
`...`	other variables for barplot method.

Eric Zivot and Yi-An Chen.

## Not run: 
# BARRA type factor model
data(Stock.df)
# there are 447 assets
exposure.names <- c("BOOK2MARKET", "LOG.MARKETCAP")
fit.fund <- fitFundamentalFactorModel(data=data,exposure.names=exposure.names,
                                       datevar = "DATE", returnsvar = "RETURN",
                                       assetvar = "TICKER", wls = TRUE,
                                       regression = "classic",
                                       covariance = "classic", full.resid.cov = TRUE,
                                       robust.scale = TRUE)

plot(fit.fund)

## End(Not run)