fPortfolio (version 260.72)

PortfolioSpec: Specification of Portfolios

Description

A collection and description of functions to specify a portfolio. Typical specifications include model settings, portfolio parameters, and selection of the type of solver. The functions are: ll{ portfolioSpec Specifies a portfolio, setType Sets type of portfolio optimization, setEstimator Sets names of mean and covariance estimators, setParams Sets optional model parameters, setWeights Sets weights vector, setTargetReturn Sets target return value, setTargetAlpha Sets CVaR target alpha value, setRiskFreeRate Sets risk-free rate value, setNFrontierPoints Sets number of frontier points, setNFrontierPoints Sets tail dependence matrix, portfolioStatistics Estimates 'mu' and 'Sigma' statistics, print|show Print method for fPFOLIOSPEC objects. }

Usage

portfolioSpec(model = list(type = c("MV", "CVaR"), estimator = c("mean", "cov"), 
    tailRisk = list(), params = list()), portfolio = list(weights = NULL, 
    targetReturn = NULL, targetRisk = NULL, targetAlpha = 0.05, riskFreeRate = 0, 
    nFrontierPoints = 50),solver = list(solver = c("quadprog", "Rdonlp2", 
    "lpSolve"), trace = FALSE))
show.fPFOLIOSPEC(object)
setType(spec) <- value
setEstimator(spec) <- value
setParams(spec) <- value
setWeights(spec) <- value
setTargetReturn(spec) <- value
setTargetAlpha(spec) <- value
setRiskFreeRate(spec) <- value
setNFrontierPoints(spec) <- value
setTailRisk(spec) <- value
setSolver(spec) <- value
setTrace(spec) <- value

Arguments

estimator

[setEstimator] - a character string vector, determining which estimation type should be used calculating mean and covariance matrix, by default "mean" and "cov" meaning functions mean() and cov(). Other estimators are "mcd", using

model

[portfolioSpec] - a list, containing different arguments: type, estimator, params. See these arguments for further explanation.

nFrontierPoints

[setNFrontierPoints] - a numeric, determining the number of equidistant steps on the frontier, by default 50.

object

[show] - an S4 object of class fPFOLIOSPEC, having slots call, model, portfolio, title, description. See value for slot description.

params

[setParams] - a list of optional model parameters, currently not used.

portfolio

[portfolioSpec] - a list, containing different arguments: weights, targetReturn, riskFreeRate, nFrontierPoints. See these arguments for further explanation.

riskFreeRate

[setRiskFreeRate] - a integer value, determining the percentage of the yearly return for a risk free asset.

solver

a character string denoting the type of the solver to be used.

spec

an S4 object of class fPFOLIOSPEC, the specification to be modified, by default the default of the function portfolioSpec().

tailRisk

a list with two matrices for the upper and lower tail dependence coefficients.

targetAlpha

[setTargetAlpha] - a numerical value, setting the desired portfolio CVaR alpha.

targetReturn

[setTargetReturn] - a numerical value, setting the desired portfolio return, by default return of the tangency portfolio.

targetRisk

[setTargetRisk] - a numerical value, setting the desired portfolio risk, only for the dual portfolio calculation.

type

[setType] - a character string, determining which risk measure should be taken, by default "MV" meaning mean-variance. Other types are "CVaR" and "LPM".

value

a value for that component of spec to be set.

weights

[setWeights] - a numerical vector, containing the weights of the desired optimal portfolio. Note that the program stops if desired return and weights are set.

Value

• portfolioSpec returns an S4 object of class "fPFOLIOSPEC".

  setType setEstimator Model Settings: just modify the model settings including the portfolio type, the mean/covariance estimator, and optional parameters of an existing portfolio structure. setWeights setTargetReturn setRiskFreeRate setNFrontierPoints setReturnRange setRiskRange Portfolio Settings: just modify the portfolio settings including predefined weights, the target return, the risk free rate, the number of frontier points, and the return and risk range of an existing portfolio structure. setSolver Solver Settings: just modifies the solver setting, i.e. the type of solver to be used for portfolio optimization.

Details

Portfolio Specifcation Structure: The S4 class fPFOLIOSPEC specifies the portfolio. The slots are: [object Object],[object Object],[object Object],[object Object],[object Object],[object Object] The function portfolioSpec() sets the values for the default specification structure. The default settings can be modified using the assignment functions for the specification structure. Model: Type: The risk measure in use is determined by the argument model$type. Available measures are mean-variance/Markowitz "MV", later we will add lower partial moments LPM and conditional value at risk "CVaR". Estimators: The estimator(s) for the mean vector and covariance matrix are determined by the argument model$type, which is a character vector with two elements, the first for the mean and the second for the covariance matrix. Valid pairs for example are c("mean","cov"), c("mean","shrink"), or c("mean","mcd"). The latter two covariance estimators are robust covariance estimators which are recommended to be used for portfolios with many assets and few number of data records. Portfolio: This slot sets portfolio parameters including weights, target return, risk free rate, and number of frontier points. Note, only one of portfolio$weights or targetReturn can be set exclusively. If one of both is set, the other will be set to NULL. Solver: The default solver is the quadratic programming solver from the contributes R package quadprog, Optionally, one can use the sequential quadratic programming algorithm from Spelucci as implemented in the contributed R package Rdonlp2. Note, this package is not part of the Rmetrics software and has to be installed separately. In the case of non-linear risk budget constraints which can can be handled by quadprog, one has to use Rdonlp2.

See Also

PortfolioData, PortfolioConstraints, fPORTFOLIO, PortfolioPlots.

Examples

## portfolioSpec -
   # Show Default Portfolio Specifications:
   Spec = portfolioSpec()
   # Change Risk Free Rate
   setRiskFreeRate(Spec) = 3
   Spec

## portfolioStatistics -
   # Load Data, i.e. a List of Returns:
   Data = as.timeSeries(data(smallcap.ts))
   Data = Data[, c("BKE", "GG", "GYMB", "KRON")]
   Data
   # Estimating Mean and Covariance with mean()and cov()
   portfolioStatistics(Data)
   # Set Covariance Estimator to "shrink" Estimator:
   setEstimator(Spec) = c("mean", "shrink")
   # Estimating Mean and Covariance MCD
   portfolioStatistics(Data, Spec)