[GSoC-PortA] Mean-mETL objective?

[Ross Bennett]

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
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