[GSoC-PortA] Some feedback...
Ross Bennett
rossbennett34 at gmail.com
Tue Sep 24 06:09:56 CEST 2013
On Mon, Sep 23, 2013 at 1:19 PM, Peter Carl <peter at braverock.com> wrote:
> Here's your comment from below:
>
> "It is tough to tell with the formatting on the email, but I'll take a
> closer look at the script in the sandbox to see if I can tell what is
> going on. The idea is that extractObjectiveMeasures will return a matrix
> of the objective measures for all optimize.portfolio objects in the
> opt.list object. For example, the meanSD row should have NAs under the ETL
> and ETL component contribution columns. I am only stitching together the
> objective measures, I do not re-calculate StdDev or component StdDev for
> the portfolios with ETL as an objective. Basically, I just take whatever
> objectives are in the $objective_measures slot of each optimize.portfolio
> object. Should I be doing something such that all cells in the matrix have
> values? "
>
> I think so, although I doubt this has been well spelled out before. The
> question is: can we anticipate how to fill in these values given the
> information in each object?
>
I think we might be able to depending on how the objective measures are
calculated on the weights.
One way would be to pick out the objective names, match the name to the
function, and then calculate the objectives on the weights. The parameters
could be pulled from the $arguments list in each objective. This might be
tricky if there are multiple arguments with different arguments. This is
likely the simplest solution. If "ES" is an objective name, we could by
default calculate it with portfolio_method="component" since the univariate
ES also calculated.
Another way is to combine all the objectives from each object, try to
detect and remove duplicate objectives objects, then pass that portfolio
object to constrained_objective to calculate over the weights.
Not sure which way is better, I'll have to give this some thought and try
out a few things.
>
> When I do this by hand, I'm just calculating for the list of optimal
> weights of each objective for each measure. At that point, I can make
> comparisons I couldn't otherwise.
>
> Note that the objectives can be vastly different, as long as the assets
> are the same and the parameters for each of the metrics are the same.
>
I could add a check to make sure that the assets and returns are the same
in each optimize.portfolio object. I think this will only work if that is
the case. It would be nice to have the flexibility to have different assets
and returns, but that may not be doable.
>
> Does that make sense?
>
It does make sense, thanks for the feedback.
>
> pcc
> --
> Peter Carl
> http://www.braverock.com/peter
>
> > Peter,
> >
> > Thanks for the feedback, I really appreciate it.
> >
> > see comments in line.
> >
> >
> > On Sun, Sep 22, 2013 at 4:41 PM, Peter Carl <peter at braverock.com> wrote:
> >
> >> Ross,
> >>
> >> I've been working through your vignette to hopefully give you some more
> >> detailed feedback, including on your questions from a few days ago.
> >> Sorry
> >> this has taken so long, but I wanted to spend some focused time on the
> >> package.
> >>
> >> I realize that you've got different plot methods for each type, and I
> >> appreciate what a hassle it is to keep such methods relatively
> >> consistent.
> >> In chart.RiskReturn.DE, when the function doesn't find anything that
> >> fits
> >> its defaults:
> >> > plot(RiskBudget.DE)
> >> Error in plot.window(...) : need finite 'xlim' values
> >> In addition: Warning messages:
> >> 1: In chart.Scatter.DE(object = DE, risk.col = risk.col, return.col =
> >> return.col, :
> >> mean or ES do not match extractStats output of $objective_measures
> >> slot
> >> 2: In min(x) : no non-missing arguments to min; returning Inf
> >> 3: In max(x) : no non-missing arguments to max; returning -Inf
> >>
> >> It's a risk budget on ETL, so if I tell it that, it works:
> >> > plot(RiskBudget.DE, risk.col="ETL", return.col="mean")
> >>
> >
> > The default is risk.col="ES". Because your objective name is "ETL", you
> > need to explicitly do risk.col="ETL".
> >
> >
> >>
> >> ...but it doesn't recover well when I try to plot the results in
> >> variance
> >> space:
> >> > plot(RiskBudget.DE, risk.col="StdDev", return.col="mean")
> >> Error in plot.window(...) : need finite 'xlim' values
> >> In addition: Warning messages:
> >> 1: In chart.Scatter.DE(object = DE, risk.col = risk.col, return.col =
> >> return.col, :
> >> mean or StdDev do not match extractStats output of
> >> $objective_measures
> >> slot
> >> 2: In min(x) : no non-missing arguments to min; returning Inf
> >> 3: In max(x) : no non-missing arguments to max; returning -Inf
> >>
> >>
> >> I'm not exactly sure what the issue is here, but maybe it's related:
> >> > chart.RiskBudget(RiskBudget.DE, risk.type="percentage", neighbors=5)
> >> Error in subsetx[i, riskcols] : incorrect number of dimensions
> >> > traceback()
> >> 3: points(subsetx[i, riskcols], type = "b", col = "lightblue")
> >> 2: chart.RiskBudget.optimize.portfolio(RiskBudget.DE, risk.type =
> >> "percentage",
> >> neighbors = 5)
> >> 1: chart.RiskBudget(RiskBudget.DE, risk.type = "percentage", neighbors =
> >> 5)
> >>
> >
> > Not sure either what the issue is, but I'll take a look.
> >
> >
> >> In chart.RiskReturnScatter.RP, it looks like 'rp' is being passed into
> >> plot through dots.
> >> > plot(EqmETL.RND, risk.col="StdDev", return.col="mean", rp=1000,
> >> chart.assets=TRUE)
> >> There were 13 warnings (use warnings() to see them)
> >> > warnings()
> >> Warning messages:
> >> 1: "rp" is not a graphical parameter
> >> 2: "rp" is not a graphical parameter
> >> 3: "rp" is not a graphical parameter
> >>
> >
> > The 'rp' argument is meant for optimize.portfolio.ROI and
> > optimize.portfolio.GenSA objects. Since ROI and GenSA do not return trace
> > information like DEoptim or random portfolios, I added this as an option
> > to
> > generate random portfolios to plot the feasible space. If you are already
> > passing in an optimize.portfolio.random object, there is no need to pass
> > in
> > rp as an argument.
> >
> >
> >>
> >>
> >> > extractWeights(buoys)
> >> Convertible Arbitrage Equity Market Neutral Fixed Income
> >> Arbitrage Event Driven CTA Global Global Macro Long/Short Equity
> >> MeanSD 0.05000000 0.050
> >> 0.050 0.30000000 0.0500000 0.2000000 0.300
> >> MeanmETL 0.05000000 0.300
> >> 0.050 0.05000000 0.2000000 0.3000000 0.050
> >> MinSD 0.06042904 0.300
> >> 0.300 0.05234676 0.1735858 0.0636384 0.050
> >> MinmETL 0.05000000 0.300
> >> 0.050 0.05000000 0.2000000 0.3000000 0.050
> >> EqSD 0.12500000 0.240
> >> 0.200 0.08500000 0.1050000 0.1700000 0.075
> >> EqmETL 0.06000000 0.265
> >> 0.165 0.09000000 0.2050000 0.1300000 0.080
> >> RB 0.05200000 0.410
> >> 0.060 0.05200000 0.1438995 0.2220000 0.058
> >>
> >> ...but this doesn't:
> >> > extractObjectiveMeasures(buoys)
> >> mean StdDev ES StdDev.contribution1
> >> StdDev.contribution2 StdDev.contribution3
> >> StdDev.contribution4
> >> MeanSD 0.006782814 0.01546759 NA NA
> >> NA NA NA
> >> MeanmETL 0.005897789 NA 0.01505626 NA
> >> NA NA NA
> >> MinSD NA 0.01009001 NA NA
> >> NA NA NA
> >> MinmETL NA NA 0.01505626 NA
> >> NA NA NA
> >> EqSD NA 0.01113716 NA 0.001763096
> >> 0.001565752 0.001886988 0.001258567
> >> EqmETL NA NA 0.01646509 NA
> >> NA NA NA
> >> RB 0.005812997 NA NA NA
> >> NA NA NA
> >> StdDev.contribution5 StdDev.contribution6 StdDev.contribution7
> >> StdDev.pct_contrib_StdDev1 StdDev.pct_contrib_StdDev2
> >> MeanSD NA NA NA
> >> NA NA
> >> MeanmETL NA NA NA
> >> NA NA
> >> MinSD NA NA NA
> >> NA NA
> >> MinmETL NA NA NA
> >> NA NA
> >> EqSD 0.001039908 0.002296903 0.001325947
> >> 0.1583075 0.1405881
> >> EqmETL NA NA NA
> >> NA NA
> >> RB NA NA NA
> >> NA NA
> >> ...snip...
> >>
> >>
> > It is tough to tell with the formatting on the email, but I'll take a
> > closer look at the script in the sandbox to see if I can tell what is
> > going
> > on. The idea is that extractObjectiveMeasures will return a matrix of the
> > objective measures for all optimize.portfolio objects in the opt.list
> > object. For example, the meanSD row should have NAs under the ETL and ETL
> > component contribution columns. I am only stitching together the
> objective
> > measures, I do not re-calculate StdDev or component StdDev for the
> > portfolios with ETL as an objective. Basically, I just take whatever
> > objectives are in the $objective_measures slot of each optimize.portfolio
> > object. Should I be doing something such that all cells in the matrix
> have
> > values?
> >
> >
> >> As a consequence, only one portfolio appears in the following plot
> >> (MeanSD):
> >> > chart.RiskReward(buoys)
> >>
> >
> > This relates to my comment above about how I am not recalculating
> > anything.
> > Before the portfolios are plotted in risk-return space, I omit rows that
> > have NA values. For example, if you wanted to plot all the portfolios in
> > mean-ETL space, all portfolios should have mean and ETL as an objective.
> > You could set the multiplier to 0 so it does not affect the optimization,
> > but is returned in the $objective_measures slot.
> >
> >
> >>
> >> All in all, this is all looking good. I've got some scripts checked in
> >> under sandbox/symposium2013 if you want to follow along.
> >>
> >
> > I'll take a closer look and follow along, thanks!
> >
> >
> >>
> >> pcc
> >> --
> >> Peter Carl
> >> http://www.braverock.com/peter
> >>
> >>
> >> _______________________________________________
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> >> GSoC-PortA at lists.r-forge.r-project.org
> >> http://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/gsoc-porta
> >>
> >
>
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