assetsSim {fAssets} | R Documentation |
Simulates multivariate artificial data sets of assets, from a multivariate normal, skew normal, or (skew) Student-t distribution.
assetsSim(n, dim = 2, model = list(mu = rep(0, dim), Omega = diag(dim), alpha = rep(0, dim), df = Inf), assetNames = NULL)
n |
integer value, the number of data records to be simulated. |
dim |
integer value, the dimension (number of columns) of the assets set. |
model |
a list of model parameters: mu a vector of mean values, one for each asset series, Omega the covariance matrix of assets, alpha the skewness vector, and df the number of degrees of freedom which is a measure for
the fatness of the tails (excess kurtosis). For a symmetric distribution alpha is a vector of zeros.
For the normal distributions df is not used and set to
infinity, Inf . Note that all assets have the same value
for df .
|
assetNames |
[assetsSim] - a vector of character strings of length dim allowing
for modifying the names of the individual assets.
|
assetsSim()
returns a data.frame of simulated assets.
Adelchi Azzalini for R's sn
package,
Torsten Hothorn for R's mtvnorm
package,
Diethelm Wuertz for the Rmetrics port.
Azzalini A. (1985); A Class of Distributions Which Includes the Normal Ones, Scandinavian Journal of Statistics 12, 171–178.
Azzalini A. (1986); Further Results on a Class of Distributions Which Includes the Normal Ones, Statistica 46, 199–208.
Azzalini A., Dalla Valle A. (1996); The Multivariate Skew-normal Distribution, Biometrika 83, 715–726.
Azzalini A., Capitanio A. (1999); Statistical Applications of the Multivariate Skew-normal Distribution, Journal Roy. Statist. Soc. B61, 579–602.
Azzalini A., Capitanio A. (2003); Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skew-t Distribution, Journal Roy. Statist. Soc. B65, 367–389.
Genz A., Bretz F. (1999); Numerical Computation of Multivariate t-Probabilities with Application to Power Calculation of Multiple Contrasts, Journal of Statistical Computation and Simulation 63, 361–378.
Genz A. (1992); Numerical Computation of Multivariate Normal Probabilities, Journal of Computational and Graphical Statistics 1, 141–149.
Genz A. (1993); Comparison of Methods for the Computation of Multivariate Normal Probabilities, Computing Science and Statistics 25, 400–405.
Hothorn T., Bretz F., Genz A. (2001); On Multivariate t and Gauss Probabilities in R, R News 1/2, 27–29.
Wuertz, D., Chalabi, Y., Chen W., Ellis A. (2009); Portfolio Optimization with R/Rmetrics, Rmetrics eBook, Rmetrics Association and Finance Online, Zurich.
MultivariateDistribution
.
## LPP - # Percentual Returns: LPP = 100 * as.timeSeries(data(LPP2005REC))[, 1:3] colnames(LPP) ## assetsFit - # Fit a Skew-Student-t Distribution: fit = assetsFit(LPP) print(fit) # Show Model Slot: print(fit@model) ## assetsSim - # Simulate set with same statistical properties: set.seed(1953) lppSim = assetsSim(n = nrow(LPP), dim = ncol(LPP), model = fit@model) colnames(lppSim) <- colnames(LPP) rownames(lppSim) <- rownames(LPP) head(lppSim) head(as.timeSeries(lppSim))