[GSoC-PortA] Mean-mETL objective?

[Doug Martin]

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
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