Message: 4
Date: Fri, 02 Oct 2009 19:57:58 +0100
From: Patrick Burns <patrick at burns-stat.com>
Subject: Re: [R-SIG-Finance] Static Portfolio Optimization
To: Jorge Nieves <jorge.nieves at moorecap.com>
Cc: r-sig-finance at stat.math.ethz.ch, jessevel at andrew.cmu.edu
Message-ID: <4AC64D36.5010003 at burns-stat.com>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Jorge Nieves wrote:
Thanks for your responses. I found the function "portfolio.optim" and
the tseries series package [...] However, I still do not see how to
pass into the function the vector of expected values and the covariance
matrix.
[...]
This bothers me on two counts:
1) computational
2) subject matter
That Jorge is not finding the functionality
that he wants means that modular programming
is not being used. The modular approach
would have a function that does the optimization
with the expected returns and variance as
arguments. That function would then be
used by a function that does the larger task.
Okay, an advantage of R is that it is generally
easy to modify functions for your own purposes.
But it is better to organize ocmputations so
that people don't feel compelled to do that.
Let's abandon the SAS monolith culture.
I haven't investigated the functions that are
under discussion, so perhaps I am misunderstanding
what they are doing. But if they are using the
history of returns to predict future returns, that
is almost always going to be pretty much complete
nonsense -- with or without the Efficient Market
Hypothesis.
I would hope the R community embrace quality in
subject matter decisions as well as computational
quality.
Patrick Burns
patrick at burns-stat.com
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of "The R Inferno" and "A Guide for the Unwilling S User")