[GSoC-PortA] structure of the specification objects

[Ross Bennett]

Re: Turnover Objective Function

I have gone through the slides and code, but did not see an example using
turnover as an objective function.
http://www.rinfinance.com/**agenda/2010/Carl+Peterson+**Boudt_Tutorial.pdf<http://www.rinfinance.com/agenda/2010/Carl+Peterson+Boudt_Tutorial.pdf>
https://r-forge.r-project.org/**scm/viewvc.php/*checkout*/pkg/**
PortfolioAnalytics/sandbox/**script.workshop2010.R?root=**returnanalytics<https://r-forge.r-project.org/scm/viewvc.php/*checkout*/pkg/PortfolioAnalytics/sandbox/script.workshop2010.R?root=returnanalytics>

I have also gone through this presentation and code, but it does not look
like turnover was used as an objective measure.
http://www.rinfinance.com/agenda/2012/workshop/Carl+Peterson.pdf
https://r-forge.r-project.org/scm/viewvc.php/pkg/PortfolioAnalytics/sandbox/script.workshop2012.R?view=markup&root=returnanalytics

Slide 36 shows a chart of Turnover from Equal Weight, but it looks to be
that the turnover was calculated ex-post. Is there a different example you
have where turnover is specified as an objective function for the
optimization?

Both presentations have some great examples and charts for visualization
that I can use for later this summer.

Thanks,
Ross Bennett


On Tue, Jun 18, 2013 at 4:28 AM, Brian G. Peterson <brian at braverock.com>wrote:

> On 06/18/2013 03:34 AM, Kris Boudt wrote:
>
>> Intrinsically, it means that what we used to call "soft constraints"
>> (the constraints that can be violated) are classified as
>> "objectives". Seems good to me, but we need to make sure that each
>> objective has then its multiplier/scaling factor, which by default is
>> 1, but for soft constraints will typically be higher.
>>
>
> I've never liked the 'soft constraints' construct, as it's not very
> clear.  My distinction was between things we can do *before* calling the
> objective function, only on the weights vector, which we'll call
> 'constraints' and things that we can do only by acting on the set of all
> possible weights vectors which satisfy the constraints (the objectives).
>
> We've always supported both multipliers and penalties for the individual
> objectives, from the very first version of the code.  In practice, two
> things go into selecting a multiplier:
>
> a. the objectives must inherently be of similar scale, e.g. both returning
> a return number of roughly equal magnitude.  if they are not of roughly
> equal magnitude, then the user needs to use the multiplier to adjust.
>
> b. the user must understand that to over/under weight a specific objective
> with respect to other objectives, they need to adjust either the multiplier
> or the penalty, or both.
>
>
>  1. I would also include a turnover objective, whereby there seem to
>> be two possibilities:
>>
>> - provide directly the weights at the time of rebalancing - provide
>> the weights at the previous rebalancing data and include a function
>> that, uses the return data to calculate the weights at the time of
>> rebalancing.
>>
>
> We demonstrated how to use a turnover objective function in our 2012
> R/Finance seminar:
>
> http://www.rinfinance.com/**agenda/2010/Carl+Peterson+**Boudt_Tutorial.pdf<http://www.rinfinance.com/agenda/2010/Carl+Peterson+Boudt_Tutorial.pdf>
>
> see page 36
>
> with code here:
> https://r-forge.r-project.org/**scm/viewvc.php/*checkout*/pkg/**
> PortfolioAnalytics/sandbox/**script.workshop2010.R?root=**returnanalytics<https://r-forge.r-project.org/scm/viewvc.php/*checkout*/pkg/PortfolioAnalytics/sandbox/script.workshop2010.R?root=returnanalytics>
>
> It would be nice to get the chart from page 36 into the package if we have
> time later in the summer.
>
> In practice, turnover can be dealt with either as a constraint (in some
> solvers) or as an objective.  Doug would need to comment on using it as a
> constraint, I know there's a brief discussion of that in MPO(v1) or perhaps
> Bernd's book, both of which I have at the office right now.
>
> I've always done it as an objective, which works fine in current code.
>
> It would probably be nice to include the turnover function in the package
> directly and document it.
>
>
>  2. In practical work,  I work with a price data file that has all
>> possible constituents and for each selection date a list of allowed
>> constituents. Typically an xts with in row the selection dates and
>> columns the assets with 1 if included and 0 otherwise. Such a
>> constituents check could be in the constraints object.
>>
>
> It seems to me that this belongs in the portfolio specification.  That is
> to say that the constituents of the portfolio are defined in the portfolio
> specification as a time series.
>
> Another way to think of this, of course, is to say that an equality
> constraint (weight=0) is imposed on some of the overall universe of
> constituents at certain times.  You can also do it with box constraints
> that vary through time.
>
> I think I prefer the first approach as more intuitive for the user, and
> dealing with subsetting the input data to match the allowed constituents
> within optimize.portfolio.  We're better off never giving data to the
> solvers that they don't need, and if the constituent is out of the
> portfolio, then the subset can happen before the optimization step. That's
> just an initial feeling though.
>
> I think we need to think more about what it does to the code to support
> time-varying constraints and portfolio specifications, and then put it
> wherever it makes the most sense.  I don't see any reason to work on that
> this week though, as the overall structure seems more important to me at
> this point, and I think we can cover this when we have a more coherent
> framework to work from.
>
> Regards,
>
> Brian
>
>
> --
> Brian G. Peterson
> http://braverock.com/brian/
> Ph: 773-459-4973
> IM: bgpbraverock
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