solveRshortExact         package:fPortfolio         R Documentation

_E_x_a_t _u_n_l_i_m_i_t _S_h_o_r_t _S_e_l_l_i_n_g _S_o_l_v_e_r

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

     Optimizes an unlimited short selling portfolio  analytically.

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

     solveRshortExact(data, spec, constraints)

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

    data: a time series or a named list, containing either a series of
          returns  or named entries 'mu' and 'Sigma' being mean and
          covariance matrix. 

    spec: an S4 object of class 'fPFOLIOSPEC' as returned by the
          function 'portfolioSpec'. 

constraints: a character string vector, containing the constraints of
          the form
           '"minW[asset]=percentage"' for box constraints resp. 
           '"maxsumW[assets]=percentage"' for sector constraints. 

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

     a list with the following named ebtries:  'solver',  'optim',
     'weights', 'targetReturn', 'targetRisk',  'objective', 'status',
     'message'.

_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:

     ## data - 
        Data = SMALLCAP.RET
        Data = Data[, c("BKE", "GG", "GYMB", "KRON")]
        Data
        
     ## spec - 
        Spec = portfolioSpec()
        setSolver(Spec) = "solveRshortExact" 
        setTargetReturn(Spec) = mean(Data)
        Spec

     ## constraints - 
        Constraints = "LongOnly"
              
     ## solveRshortExact -
        solveRshortExact(Data, Spec, Constraints)

