 Usage:  VaR = VaRpred(y{,method}{,opt})  

 

 Input:



  y                      n x d matrix, the returns of d assets. 

                         

  method                 method for VaR, one of 

                         "BETA" (beta factor model), 

                         "BETACOR" (corrected beta factor model), 

                         "PRINC" (principal components), 

                         "PRINCW" (weighted principal components). 

                         "SUMS" (sums of uncorrelated variables). 

                         "COMPLETE" (no reduction of variance matrix). 

                         default is the "COMPLETE" option, the beta 

                         factor models assume that the first column 

                         in the data matrix is the index. 

                         

  opt                    optional, a list with optional input. The macro 

                         "VaRopt" can be used to set up this parameter. 

                         The order of the list elements is not important. 

                         Parameters which are not given are replaced by 

                         defaults (see below). 

                         

  opt.alpha              scalar in (0,1), significance level. The 

                         default is 0.01. 

                         

  opt.w                  scalar, 1 x d or n+1 x d, weights for assets. 

                         If not given, set to 1, the first coordinate 

                         is not used in computation for beta factor models. 

                         

 Output:



  VaR                    1 x 2 vector, the VaR for observation n+1. 

                         

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(C) MD*TECH Method and Data Technologies, 21.9.2000

