covEstimator           package:fPortfolio           R Documentation

_C_o_v_a_r_i_a_n_c_e _E_s_t_i_m_a_t_o_r_s

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

     Functions to estimate and robustify the sample  mean and
     covariance of rectangular objects.

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

     covEstimator(x, spec = NULL, ...)
     mveEstimator(x, spec = NULL, ...)
     mcdEstimator(x, spec = NULL, ...)

     lpmEstimator(x, spec = NULL, ...)

     kendallEstimator(x, spec = NULL, ...)
     spearmanEstimator(x, spec = NULL, ...)

     covMcdEstimator(x, spec = NULL, ...)
     covOGKEstimator(x, spec = NULL, ...)
     shrinkEstimator(x, spec = NULL, ...)
     nnveEstimator(x, spec = NULL, ...)

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

       x: an object of class 'timeSeries'.  

    spec: unused, may be used to pass information from the portfolio
          specification object to the mean and covariance estimator
          function. 

     ...: optional arguments to be passed to the underlying estimators.            

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

     The functions are underlying the following algorithms:

     'covEstimator' uses standard covariance estimation,
      'mveEstimator' uses the function "cov.mve" from the MASS package,
      'mcdEstimator' uses the function "cov.mcd" from the MASS package,
      'lpmEstimator' returns lower partial moment estimator,
      'kendallEstimator' returns Kendall's rank estimator,
      'spearmanEstimator' returns Spearman's rankestimator,
      'covMcdEstimator' requires "covMcd" from package robustbase,
      'covOGKEstimator' requires "covOGK" from package robustbase,
      'nnveEstimator' uses builtin from package covRobust,
      'shrinkEstimator' uses builtin from package corpcor.

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

     the functions return a list with two entries named 'mu' and 
     'Sigma'. The first denotes the vector of column means, and the
     second the  covariance matrix. Note, that the output of this
     function can be used as data input for the portfolio functions to
     compute the efficient frontier.

_A_u_t_h_o_r(_s):

     ... for R's 'MASS' package, 
      ... for R's 'robustbase' package, 
      ... for R's 'covRobust' package, 
      Juliane Schaefer and Korbinian Strimmer for R's 'corpcor'
     package, 
      Diethelm Wuertz for this Rmetrics port.

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

     Breiman L. (1996);  _Bagging Predictors_, Machine Learning 24,
     123-140.

     Ledoit O., Wolf. M. (2003); _ImprovedEestimation of the Covariance
     Matrix of Stock Returns  with an Application to Portfolio
     Selection_, Journal of Empirical Finance 10, 503-621. 

     Schaefer J., Strimmer K. (2005);   _A Shrinkage Approach to
     Large-Scale Covariance Estimation and Implications for Functional
     Genomics_, Statist. Appl. Genet. Mol. Biol. 4, 32.

     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 -
        colnames(SMALLCAP.RET)
        
     ## covEstimator -
        covEstimator(SMALLCAP.RET)
        
     ## shrinkEstimator -
        # shrinkEstimator(SMALLCAP.RET)

