returns=[12 8 50];
STDs=[24.559 32.009 113.92];
correlations=[1 0 0;0 1 0;0 0 1];
covariances = corr2cov(STDs , correlations);
variances = corr2cov(STDs , correlations);
portopt(returns , covariances , 20);
[PortRisk, PortReturn, PortWts] = frontcon(returns,covariances,20);
[PortRisk, PortReturn, PortWts]
警告: In a future release, portopt will undergo a change to solve only
the default portfolio problem for long-only fully-invested portfolios.
To solve more general problems, use the Portfolio object.
See the release notes for details, including examples to make the conversion. 
警告: In a future release, frontcon will be removed. Use the Portfolio object
instead.
See the release notes for details, including examples to make the conversion. 
警告: In a future release, portopt will no longer accept ConSet or varargin
arguments.
'It will only solve the portfolio problem for long-only fully-invested
portfolios.
To solve more general problems, use the Portfolio object.
See the release notes for details, including examples to make the conversion. 

ans =

   19.2058   11.6400    0.6116    0.3600    0.0284
   20.0269   13.6590    0.6211    0.3033    0.0756
   22.3096   15.6779    0.6306    0.2466    0.1227
   25.6669   17.6968    0.6401    0.1900    0.1699
   29.7370   19.7158    0.6497    0.1333    0.2171
   34.2669   21.7347    0.6592    0.0766    0.2642
   39.0970   23.7537    0.6687    0.0199    0.3114
   44.1582   25.7726    0.6376         0    0.3624
   49.4695   27.7916    0.5844         0    0.4156
   54.9653   29.8105    0.5313         0    0.4687
   60.5955   31.8295    0.4782         0    0.5218
   66.3259   33.8484    0.4250         0    0.5750
   72.1325   35.8674    0.3719         0    0.6281
   77.9984   37.8863    0.3188         0    0.6812
   83.9111   39.9053    0.2657         0    0.7343
   89.8613   41.9242    0.2125         0    0.7875
   95.8422   43.9432    0.1594         0    0.8406
  101.8483   45.9621    0.1063         0    0.8937
  107.8753   47.9811    0.0531         0    0.9469
  113.9200   50.0000         0         0    1.0000