[GSoC-PortA] Mean-mETL objective?

Mon Oct 7 17:51:48 CEST 2013

Ross,

OK, I see what you mean.   Do keep in mind the following:

1)      Before a search is done the code should check that the mean return
of the global minimum ETL (under constraints) - I call this GMETL is less
than the risk free rate (which may be zero by default).  Otherwise the
search is useless as there is no tangent portfolio (well I have to be a
little careful, this is definitely the case for the MVO efficient frontier
without constraints and most likely with most constraints, and ditto for the
mean-ETL efficient frontier).  By this ratio is known as the STARR ratio in
the literature.

2)      If in your second paragraph do you mean that is the default
behavior?  If so there should be a default argument whose default is
"maxSTARR", but the user should also be able to choose GMETL.

Doug

From: gsoc-porta-bounces at lists.r-forge.r-project.org
[mailto:gsoc-porta-bounces at lists.r-forge.r-project.org] On Behalf Of Ross
Bennett
Sent: Monday, October 07, 2013 8:30 AM
To: PortfolioAnalytics
Subject: Re: [GSoC-PortA] Mean-mETL objective?

Doug,

I don't think you were missing anything, perhaps I misunderstood. From
previous emails in this thread, I thought that there was a way to formulate
the mean/ETL as an LP problem that would avoid having to do a search for the
maximum mean/ETL portfolio. There is no need to do this for DEoptim or
random portfolios, I was just referring to maximizing mean/ETL using ROI. 

I implemented this as of commit r3212. If mean and ETL (also ES or CVaR) are
objectives and optimize_method="ROI", the optimal portfolio returned is one
that maximizes mean/ETL. I use a bisection search to find the portfolio that
maximizes mean/ETL.

Ross

On Sun, Oct 6, 2013 at 6:11 PM, Doug Martin <martinrd at comcast.net> wrote:

Maybe I'm missing something, and you are concerned about something more than
just mean-ETL optimization, i.e., using random portfolios or DeOptim due to
constraints???     

As for the STARR ratio Step 3 is fine, and can also be used for max Sharpe
ratio.  As long as the efficient frontier is concave  both ratios increase
until the maximum and then decrease, so a simple line search will work and
converge pretty rapidly.  I have a placeholder for a max SR section in
Chapter 2 and will do soon.  

Am I missing something?

Doug

From: gsoc-porta-bounces at lists.r-forge.r-project.org
[mailto:gsoc-porta-bounces at lists.r-forge.r-project.org] On Behalf Of Ross
Bennett
Sent: Sunday, October 06, 2013 5:56 PM
To: PortfolioAnalytics

Subject: Re: [GSoC-PortA] Mean-mETL objective?

It will be nice if there is a simple way to formulate this as an LP problem
to maximize mean/ETL. If there is not a simple formulation, one way to
approach this would be similar to finding the tangency portfolio on the
efficient frontier. Generating a finite number of portfolios along the
frontier and finding the portfolio with the highest mean/ETL will find the
approximate tangency portfolio and is what I do for the efficient frontier
code.

Step 1: Calculate the minimum ETL portfolio given the constraints. This is
the minimum possible mean return.

Step 2: Calculate the maximum return portfolio given the constraints. This
is the maximum possible mean return.

Step 3: Increase or decrease the target return constraint and run the
optimization.

Repeat step 3 until we get convergence within a specified tolerance or reach
the maximum number of iterations.

I'm not sure what the right approach or method would be for step 3. Maybe
split the frontier in two equal spaces and iteratively shrink the search
space until we find a solution. 

Am I on the right track here? Any thoughts on how to do step 3?

Thanks,

Ross

On Sun, Oct 6, 2013 at 8:44 AM, Doug Martin <martinrd at comcast.net> wrote:

Will need to do an in-depth comparison of Rglpk versus Symphony LP (withMIP)
solvers.

I think you mentioned a project for evaluating the various solvers against
commonly used benchmark problems? What is the status and timing of that?

Doug

-----Original Message-----
From: gsoc-porta-bounces at lists.r-forge.r-project.org
[mailto:gsoc-porta-bounces at lists.r-forge.r-project.org] On Behalf Of Brian
G. Peterson

Sent: Sunday, October 06, 2013 8:19 AM
To: gsoc-porta at r-forge.wu-wien.ac.at
Subject: Re: [GSoC-PortA] Mean-mETL objective?

On 10/06/2013 10:00 AM, Doug Martin wrote:
> P.S. Chapter 4 in the 2nd edition on mean-ETL optimization via LP with
> Rglpk, with some nice examples (will send when available).   I will also
use
> this for the MIP examples in an advanced constraints chapter (since we
> don't have a QP solver available with MIP capability, unless I can
> find time to do a chapter using CPLEX via PortfolioAnalytics via ROI).

there is also a ROI front end to the MILP Symphony solver.

I'm not sure iof the Symphony solver includes QP constraints.

--
Brian G. Peterson
http://braverock.com/brian/
Ph: 773-459-4973
IM: bgpbraverock
_______________________________________________
GSoC-PortA mailing list
GSoC-PortA at lists.r-forge.r-project.org
http://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/gsoc-porta

_______________________________________________
GSoC-PortA mailing list
GSoC-PortA at lists.r-forge.r-project.org
http://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/gsoc-porta

_______________________________________________
GSoC-PortA mailing list
GSoC-PortA at lists.r-forge.r-project.org
http://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/gsoc-porta

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.r-forge.r-project.org/pipermail/gsoc-porta/attachments/20131007/42926129/attachment-0001.html>