[R-sig-finance] Monte Carlo and Portfolio Optimization

[Patrick Burns]

This seems like two different issues to me.

Putting a limit on the maximum weight of the assets should
alleviate the concentration that you are worried about.

The POP User's Manual (on http://www.burns-stat.com)
has a very brief section on resampling with a couple of
references, but for on-line resources I suspect that googling
for 'resampled efficient frontier' would be a good move.
The POP manual is probably more useful as background
for optimization in general than for information on resampling.


Patrick Burns
patrick at burns-stat.com
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of S Poetry and "A Guide for the Unwilling S User")

Silvia Marelli wrote:

>Hi,
>I am trying to build some realistic efficient
>portfolios using some mean/variance techniques
>(Markowitz, CAPM etc...).
>I normally end up with an unrealistic concentration of
>the wealth in a too limited number of assets.
>I heard about Monte Carlo techniques to account for
>the unaccuracy of the information available.
>What would be a good starting point?
>I am not experienced, so I need to keep it as simple
>as possible.
>Should I simply optimize many ptfs, by sampling the
>return of each asset from a distribution which I
>assume to be a Gaussian centered on the expected
>return of the asset?
>Is it possible to introduce some "noise" also in the
>covariance matrix?
>Then how should I "average out" the results?
>I am not very familiar with these techniques, so if
>anyone can suggest some online resources, I would be
>very grateful.
>Regards
>
>Silvia
>
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