fAssets (version 4023.85)

assets-modeling: Modeling Multivariate Asset Sets

Description

Fitting and Simulatingassets from multivariate asset sets based on modeling skew normal and related distributions.

Usage

assetsFit(x, method = c("st", "sn", "sc"), 
  title=NULL, description=NULL, fixed.df=NA, ...)
assetsSim(n, method=c("st", "sn", "sc"),
    model=list(beta=rep(0, 2), Omega=diag(2), alpha=rep(0, 2), nu=4), 
    assetNames=NULL)

Value

assetsFit returns the fitted parameters, assetsSim

returns a simulated (return) series.

Arguments

x

any rectangular time series object which can be converted by the function as.matrix() into a matrix object, e.g. like an object of class timeSeries, data.frame, or mts.

n

a numeric value which represents the number of random vectors to be drawn.

method

a character string with the names of the supported distributions: sn skew normal, st skew Student-t, and sc skew Cauchy

model

a list with the model parameters. beta a numeric vector, representing the location, Omega a symmetric positive-definite matrix (covariance matrix), alpha a numeric vector which regulates the skew of the density, nu a positive value representing the degrees of freedom.

fixed.df

a logical value, should the degreess of freedom fitted or held fixed?

title

an optional project title.

description

an option project desctiption.

assetNames

a character vector with optional asset names.

...

optional arguments passed to the underlying functions.

Author

Diethelm Wuertz for the Rmetrics port.

References

Wuertz, D., Chalabi, Y., Chen W., Ellis A. (2009); Portfolio Optimization with R/Rmetrics, Rmetrics eBook, Rmetrics Association and Finance Online, Zurich.

Examples

## LPP2005REC -
   # Load Swiss Pension Fund Data as Percentual Returns:
   LPP <- 100 * LPP2005REC[, 1:3]
   head(LPP)
   
## assetsFit -
   # Fit a Skew-Student-t Distribution: 
   fit <- assetsFit(LPP)
   # Extract the Model:
   model <- fit@fit$dp
   # Show Model Slot:
   print(model)
   
## assetsSim -
   # Simulate set with same statistical properties:
   set.seed(1953)
   LPP.SIM <- assetsSim(n=nrow(LPP), model=model)
   colnames(LPP.SIM) <- colnames(LPP)
   head(LPP.SIM)