[GSoC-PortA] structure of the specification objects
Doug Martin
martinrd at comcast.net
Mon Jun 17 16:57:54 CEST 2013
Brian and Ross,
I couldn't agree more with the proposal to separate constraints and
objectives (Brian, as you and I have discussed earlier this year or last
year).
I will have further comments on checking validity of adding constraints late
tomorrow or early Wed. after I have completed grading of my spring quarter
course.
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, June 17, 2013 7:09 AM
To: PortfolioAnalytics
Cc: gsoc-porta at r-forge.wu-wien.ac.at
Subject: Re: [GSoC-PortA] structure of the specification objects
Brian,
I really like your thoughts on separating constraints and objectives. I
learned objectives and constraints in the same way that you mention them.
Intuitively, it is easier to understand that the user would create the
constraint object, the objective object, and then combine in a portfolio
object.
Separating out the objectives and creating templates of objectives for
minimum variance and other basic objective functions should make it easy to
understand for the user as well how it is handled with the solvers.
The way the constraints object looks today seems to be very similar to what
you have in mind for the portfoliospec object. Was that your intent so that
the solvers see pretty much the same object in the call to
optimize.portfolio? Only now the portfoliospec object will be passed instead
of the constraints object, is my understanding of your intentions correct?
This is what I am thinking the code will look *something* like to run a
simple optimization problem.
#### Example R code
# Specify a constraints object and add box constraints
gen.constr = constraint(assets, min_sum=1, max_sum=1)
gen.constr = add.constraint(gen.constr, min_weight=0.10, max_weight=0.4,
type="box")
# Specify an objective object for global minimum variance
gen.obj = objective(type="GMV")
# Specify a portfolio object
port.spec = portfoliospec(gen.constr, gen.obj)
# Run the optimization
solution = optimize.portfolio(data, port.spec)
#####
Thanks,
Ross Bennett
On Mon, Jun 17, 2013 at 6:51 AM, Brian G. Peterson <brian at braverock.com>
wrote:
I've been thinking a lot about this over the last week, and I'm going to
propose an architecture for discussion.
Right now, we have an object of type 'constraints' which also includes
'objectives'.
I have always logically separated objectives from constraints in my head by
saying that
- constraints are something that are:
1. operable only on the weight vector and
2. metadata information about the portfolio (e.g. groups, asset names)
3. describe the *inputs* to the objective function
- objectives are part of the *objective function* that
1. you calculate on the weight vector
2. describe business objectives for the *outcome* of the optimization
I think we need to split these apart explicitly, and make the distinctions,
and why they exist, more obvious to the user.
First, I think we need a container object of type 'portfolio' or
'portfoliospec' that know what assets you have, and how you want to group
them (e.g. sectors, size, whatever). This is data about the portfolio, and
is *independent* of and constraints or objectives you might have on that
portfolio.
Next, I think we need a constraints object. Constraints, by their nature,
are tied to the portfolio that they are created for. They require knowledge
of the portfolio metadata, or at the very least things like box constraints
are typically derived from the size of the portfolio.
Finally, I think we need a separate 'objectives' object. To have objectives
objects, with names, that specify things like minimum variance, maximum
Sharpe ratio, or risk parity objectives. These can be completely separate
from the assets in the portfolio, and we could provide a number of template
objective objects with the package. I think the current way objectives are
added and manipulated is fine, we just need to break it off a bit.
For the template objectives that can be acted on by specific more efficient
solvers, I think separating the objectives out will make it easier to
identify that.
optimize.portfolio needs all three of these components, even today, to do
anything. So I think we need to sort out how to specify them, then how to
combine them.
I suggest that we start by getting these specifications right first. Then we
can start surgery in other parts of the code to use the new specification
forms.
My current thoughts are that a portfolio *contains* one or more constraints
objects, since the constraints objects are dependent on the portfolio
composition. Then you optimize a portfolio by passing a portfolio
specification into the optimizer, and telling it which constraints object to
use (if you have more than one attached to the portfolio) and what
objectives object you want to apply.
Hopefully this is clear. It's a proposal, so comments/critique/ideas always
welcome.
Today is officially the first day of coding, so we need to get moving.
Regards,
Brian
On 06/06/2013 06:54 AM, Ross Bennett wrote:
Professor Martin,
Thank you for the feedback. Based on the suggestions from yourself and
Brian Peterson, I will start with the constraints portion. I'll spend
some more time looking at Kirk Li's code to understand it better and
think about how to best integrate into PortfolioAnalytics. I should be
able to use some ideas from it.
I have been reviewing the code for PortfolioAnalytics and it seems that
there is already a lot of the infrastructure in place for the constraint
object and the optimizer so I don't want to maintain the interface to
the optimize.portfolio function as much as possible.
As an example, here is a code snippet of how box constraints and group
constraints are currently specified.
# General constraints object
# Box constraints of minimum weight = 0.1 and maximum weight = 0.5 for
assets
gen.constr <- constraint(assets = colnames(edhec), min=0.1, max =0.5,
min_sum=1, max_sum=1)
# Add group constraints to the gen.constr object
groups <- c(3,3,3,4)
gen.constr$groups <- groups
gen.constr$cLO <- rep(0.15,length(groups))
gen.constr$cUP <- rep(0.30,length(groups))
Following the outline on the GSOC2013 PortfolioAnalytics rwiki page, we
would remove box constraints from the constraint() function and create
an add.constraint() function to add/update box, group, and other
constraint types as applicable.
# Create the initial constraint object
# Pass in a character vector of asset names for assets
# Portfolio weights must sum to 1 (min_sum=1 and max_sum=1)
gen.constr <- constraint(assets = colnames(edhec), min_sum=1, max_sum=1)
# Add box constraints with asset weights greater than 0.1 and less than 0.5
gen.constr <- add.constraint(constraints=gen.constr, type="box",
min=0.1, max=0.5)
# Group constraints for 10 assets
# Separate assets into groups of 3, 3, and 4 assets
# Specify the group weights as a vector
# The first 3 assets shall have a group weight of greater than 0.15 and
less than 0.3
# The next 3 assets shall have a group weight of greater than 0.1 and
less than 0.35
# The last 4 assets shall have a group weight greater than 0 and less
than 0.4
constr <- add.constraint(constraints=constr, type="group",
groups=c(3, 3, 4),
group_min=c(0.15, 0.1, 0),
group_max=c(0.3, 0.35, 0.4))
This keeps the constraint object and interface to optimize.portfolio()
consistent with the existing code, but simplifies it and makes adding
box and group constraints very similar.
I will continue to review the PortfolioAnalytics source code and we can
revisit this so that I can hit the ground running when finals are over
and start as soon as possible.
Regards,
Ross Bennett
On Wed, Jun 5, 2013 at 9:23 AM, Doug Martin <martinrd at comcast.net
<mailto:martinrd at comcast.net>> wrote:
Ross and all,____
__ __
I think starting with the constraints is a good idea. But I think a
review of where PortfolioAnalytics functionality is as of last
year's GSoC should be the first priority. How planning on that week
after next (Guy, Eric and I all have finals week to get out of the
way next week).____
__ __
With regard to constraints, that approach that Kirk Li (UW
Statistics Ph.D. student and AMATH 543 TA this spring) developed
looks useful. Ross you already have the code which I posted to the
class web site. I have attached it here for others on this project
to have a look at. Let's review that after the end of next week
when final exams and the spring quarter are completely behind us.____
__ __
Doug____
__ __
__ __
*From:*gsoc-porta-bounces at lists.r-forge.r-project.org
<mailto:gsoc-porta-bounces at lists.r-forge.r-project.org>
[mailto: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:* Wednesday, June 05, 2013 4:22 AM
*To:* gsoc-porta at lists.r-forge.r-project.org
<mailto:gsoc-porta at lists.r-forge.r-project.org>
*Subject:* [GSoC-PortA] Schedule for PortfolioAnalytics Coding____
__ __
All,____
__ __
In my GSOC proposal, the order of what components I planned to write
code for was as follows:____
1. Utility Functions (print, summary, plot, etc.)____
2. Constraints____
3. Example Functionality____
In speaking with Brian Peterson at R/Finance, he suggested that the
constraints portion be done first. I am fine with doing constraints
first. Would you like me to submit a revised schedule and
implementation plan with constraints first?____
__ __
Thanks,____
Ross Bennett____
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