fPFOLIOSPEC-class         package:fPortfolio         R Documentation

_S_p_e_c_i_f_i_c_a_t_i_o_n _o_f _P_o_r_t_f_o_l_i_o_s

_D_e_s_c_r_i_p_t_i_o_n:

     Specifies portfolios.

_U_s_a_g_e:

            
     ## S4 method for signature 'fPFOLIOSPEC':
     show(object)

_A_r_g_u_m_e_n_t_s:

  object: an S4 object of class 'fPFOLIOSPEC'. 

_D_e_t_a_i_l_s:

     *Portfolio Specifcation Structure:* 

     The S4 class 'fPFOLIOSPEC' specifies the portfolio. The slots 
     are:


     @_c_a_l_l a call, returning the matched function call.

     @_m_o_d_e_l a list, setting the 'type' of portfolio to be optimized, 
          and the mean/covariance 'estimator' to be applied: 
           'type=c("MV","CVaR")' a character string denoting the type
          of portfolio, the implemented types are the Mean-Variance
          Markowitz Portfolio, '"MV"', and the Mean-CVaR Portfolio,
          '"CVaR"'. 
           'estimator=c("mean","cov")' a vector of two character
          strings, the first denoting the mean estimator, and the 
          second the covariance estimator. Additional meaningful 
          selections include robust covariance estimators, e.g. 
          'c("mean","mcd")', or 'c("mean","shrink")'. 
           'tailRisk=list()' a list of optional tail risk information,
          currently not used.
           'params=list()' a list of optional model parameters,
          currently not used. 

     @_p_o_r_t_f_o_l_i_o a list, settings portfolio parameters including
          predefined weights, target return, risk free rate, number of
          frontier points: 
            'weights=NULL' a numeric vector specifying the portfolio 
          weights. 
           'targetReturn=NULL' a numeric value specifying the target 
          return. The default value sets the target return. 
           'targetRisk=NULL' a numeric value specifying the target 
          risk.
           'targetAlpha=NULL' a numeric value specifying the target 
          alpha confidence level for CVaR portfolio optimization.  The
          default value sets the target return. 
           'riskFreeRate=0' a numeric value specifying the risk free 
          rate. 
             'nFrontierPoints=50' a numeric value determining the
          number of points on the efficient frontier.

     @_s_o_l_v_e_r a list, setting the type of solver to be used for
          portfolio optimization: 
            'type=c("quadprog", "Rdonlp2", "lpSolve")' a character
          string specifying the name of the solver to be used.
           'trace=FALSE' a logical flag, should the optimization be
          traced?

     @_t_i_t_l_e a title string, with a default project title. 

     @_d_e_s_c_r_i_p_t_i_o_n a character string, with a default project
          description.


_V_a_l_u_e:

     'portfolioSpec'

      returns an S4 object of class '"fPFOLIOSPEC"'.

_R_e_f_e_r_e_n_c_e_s:

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

_E_x_a_m_p_l_e_s:

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

