That worked! Thanks so much Ross. I really look forward to using this package.

-----Original Message-----

From: R-SIG-Finance [mailto:

[hidden email]] On Behalf Of Ross Bennett

Sent: Thursday, January 18, 2018 12:26 PM

To:

[hidden email]
Subject: Re: [R-SIG-Finance] PortfolioAnalytics with turnover constraint

Roger,

The "assets" argument for the portfolio.spec function should be a vector.

You are passing in a data.frame object.

Try defining your wgts object as follows wgts <- c("CA" = .1, "CTAG" = .3, "DS" = .4, "EM" = .1, "EQM" = .1)

Best,

Ross

On Thu, Jan 18, 2018 at 11:06 AM, Bos, Roger <

[hidden email]>

wrote:

> Dear All,

>

> I am trying to use the PortfolioAnalytics package to run an

> optimization with a turnover constraint. I didn't see any examples in

> the demos. The example code below runs in I set the portfolio up using equal weights:

>

> init.portf <- portfolio.spec(assets=funds)

>

> But if I instead try to use a named vector of initial weights, as

> described in the docs, as such:

>

> init.portf <- portfolio.spec(assets=wgts) # Does not work with this

> line added

>

> I get an error when I try to run the optimization:

>

> 11:57:01 > minStdDev.DE <- optimize.portfolio(R=R,

> portfolio=init.portf, optimize_method="DEoptim", search_size = 2000)

> Show Traceback

>

> Rerun with Debug

> Error in result[2, ] <- rep(1/length(seed), length(seed)) :

> incorrect number of subscripts on matrix

>

> The portfolio.spec function did take in the initial weights properly,

> as shown using the print function:

>

> 11:57:01 > print.default(init.portf)

> $assets

> CA CTAG DS EM EQM

> 1 0.1 0.3 0.4 0.1 0.1

>

> Can anyone provide me with a working example using both initial

> weights and a turnover constraint? I don't care it if uses DEoptim or

> some other optimizer, I just want to get started with something.

>

> Thanks,

>

> Roger

>

>

> library(PortfolioAnalytics)

>

> data(edhec)

> R <- edhec[, 1:5]

> colnames(R) <- c("CA", "CTAG", "DS", "EM", "EQM") funds <- colnames(R)

> wgts <- data.frame("CA" = .1, "CTAG" = .3, "DS" = .4, "EM" = .1, "EQM"

> =

> .1)

> wgts

>

> # Set up portfolio with objectives and constraints init.portf <-

> portfolio.spec(assets=funds) init.portf <- portfolio.spec(assets=wgts)

> # Does not work with this line added init.portf <-

> add.constraint(portfolio = init.portf, type="weight_sum", min_sum =

> .99, max_sum = 1.01) init.portf <- add.constraint(portfolio =

> init.portf, type="long_only") init.portf <- add.constraint(portfolio =

> init.portf, type="turnover", turnover_target = .2)

>

> # Add an objective to minimize portfolio standard deviation init.portf

> <- add.objective(portfolio=init.portf, type="risk",

> name="StdDev")

> print.default(init.portf)

>

> # Solve with DEoptim

> minStdDev.DE <- optimize.portfolio(R=R, portfolio=init.portf,

> optimize_method="DEoptim", search_size = 2000) minStdDev.DE

>

>

>

>

>

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