# [R-SIG-Finance] fPortfolio and leverage

giuseppe1.milicia at hsbcib.com giuseppe1.milicia at hsbcib.com
Thu Aug 21 15:06:09 CEST 2008

```Guys,

I'm playing a bit with fPortfolio and looking at the examples and unit
tests, it seems that the weights returned always sum up to 1.

I was wondering whether there is a way to have a leveraged portfolio with
weights summing up to W > 1. Say I target a certain risk level R and I want
the weights to be totally unconstrained. From the docs I see that
Constraints = "Short" should given me unconstrained weights:

"Short": This selection defines the case of unlimited short selling. i.e.
each weight may range
between -Inf and Inf. Consequently, there are no group constraints. Risk
budget constraints are
not included in the portfolio optimization.

But, say if I try this:

# Load Data and Convert to timeSeries Object:
Data = as.timeSeries(data(smallcap.ts))
Data = Data[, c("BKE", "GG", "GYMB", "KRON")]
Data

# Set Default Specifications:
Spec = portfolioSpec()
Spec

setTargetAlpha(Spec) = 0.6

# Allow for unlimiConstraints = "Short"ted Short Selling:
Constraints = "Short"

# Compute Short Selling Minimum Variance Portfolio
frontier = portfolioFrontier(Data, Spec, Constraint)

I seem to get always weights adding up to 1, no matter what I do...

I tried:

frontier = portfolioFrontier(Data, Spec, "maxsumW[1:22]=2")

Weights add up to 1 again.

frontier = portfolioFrontier(Data, Spec, "minsumW[1:22]=2")
frontier = portfolioFrontier(Data, Spec, "minsumW[1:22]=0.1")

The last two calls give back no portfolio. I wonder why? Is it no possible
to be leveraged/under invested?

I can't find anything of that sort on the unit tests either.

Cheers,

// Giuseppe

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