Hi,

I'm an R newbie and I've been struggling with a optimization problem for
the past couple of days now.

Here's the problem - I have a matrix of expected payouts from different
stock option strategies. Each column in my matrix represents a different
stock and each row represents the return to the strategy given a certain
market move. So the rows are not a time series of percentage returns but a
dollar payout in different expected scenarios, i.e.

Expected Return Matrix (ER) =                   stock1   stock2  .... stockn
                                               scenario1   $              $
              $
                                               scenario2   $              $
              $
                                               scenario3   $              $
              $
                                                   ...

I want to create an optimal portfolio of these strategies by applying a
vector of weights. The weights will be the number of contracts of each to
buy and won't be a percentage weighting. There are a few constraints I need
it comply with:

   - The weights have to be integers
   - The minimum portfolio return (ER* Weights) across the scenarios has to
   be greater than some negative number I specify
   - There has to be a certain minimum number of stocks in the portfolio so
   length(weights)>some number I specify.

Any help is GREATLY appreciated since I have tried so many different
functions and packages. Even if someone can just lead me to the correct
function to use that would be a great help as I've looked at optim,
solveLP, ROI package and many others.


Thanks,
S

	[[alternative HTML version deleted]]

