[R-SIG-Finance] [R-sig-finance] portfolio.optim and assets with weigth equals to zero...
Robert Iquiapaza
rbali at ufmg.br
Thu Sep 4 21:02:47 CEST 2008
Alberto,
Your data is a little bit mess because of NAs. The different 'treatment'
given to NAs by "coredata(get.hist.quote" and "as.timeSeries(returns" may
explain some of the differences in the results. You are passing different
set of returns. The first method passes a wrong returns matrix.
Good luck
Robert
--------------------------------------------------
From: "Alberto Santini" <albertosantini at gmail.com>
Sent: Thursday, September 04, 2008 12:57 PM
To: <r-sig-finance at stat.math.ethz.ch>
Subject: [R-SIG-Finance] [R-sig-finance] portfolio.optim and assets with
weigth equals to zero...
>
> After posting on R-Help it makes sense posting on r-sig-finance too.
>
> I don't understand a particular output of portfolio.optim (tseries).
> I have 4 assets and the portfolio.optim returns an asset with weight
> equals
> to zero.
> If I do a portfolio.optim with 3 assets, without the asset with weight
> equals to zero,
> it returns a completely different result.
>
> That's I would expected the same weights as the run with 4 assets.
>
> Below the code.
>
> Thanks in advance,
> Alberto Santini
>
>
> -------------------------------------
>
> require(tseries)
>
> f.mi <- coredata(get.hist.quote("F.MI", start="2006-09-03",
> compression="w",
> quote="Close"))
> eng.mi <- coredata(get.hist.quote("ENG.MI", start="2006-09-03",
> compression="w", quote="Close"))
> tis.mi <- coredata(get.hist.quote("TIS.MI", start="2006-09-03",
> compression="w", quote="Close"))
> spmib <- coredata(get.hist.quote("^SPMIB", start="2006-09-03",
> compression="w", quote="Close"))
>
> f.mi.rets <- diff(log(f.mi[1:(length(f.mi)-1)]))
> eng.mi.rets <- diff(log(eng.mi[1:(length(eng.mi)-1)]))
> tis.mi.rets <- diff(log(tis.mi[1:(length(tis.mi)-1)]))
> spmib.rets <- diff(log(spmib[1:(length(spmib)-1)]))
>
> x <- cbind(f.mi.rets, eng.mi.rets, tis.mi.rets, spmib.rets)
> res <- portfolio.optim(x);
> res$pw
>
> x2 <- cbind(f.mi.rets, eng.mi.rets, spmib.rets)
> res <- portfolio.optim(x2);
> res$pw
>
> ----------------------------------------
>
>
> I tried with Rmetrics too, but the behaviour is the same. So I am missing
> something...
> Very interesting to understand why. :)
>
> I think it's a numerical problem: maybe, zero is not zero, it's very near
> to
> zero.
>
> Regards,
> Alberto Santini
>
> -----------------------------
>
> require(fPortfolio)
> require(tseries)
>
> assets <- c(
> "F.MI",
> "ENG.MI",
> "TIS.MI",
> "^SPMIB"
> )
>
> f.mi <- get.hist.quote("F.MI", start="2006-09-03", end="2008-09-03",
> compression="w", quote="Close")
> eng.mi <- get.hist.quote("ENG.MI", start="2006-09-03", end="2008-09-03",
> compression="w", quote="Close")
> tis.mi <- get.hist.quote("TIS.MI", start="2006-09-03", end="2008-09-03",
> compression="w", quote="Close")
> spmib <- get.hist.quote("^SPMIB", start="2006-09-03", end="2008-09-03",
> compression="w", quote="Close")
>
> X <- cbind(f.mi[1:(length(f.mi)-1)], eng.mi[1:(length(eng.mi)-1)],
> tis.mi[1:(length(tis.mi)-1)], spmib[1:(length(spmib)-1)])
> colnames(X) <- assets
>
> R <- as.timeSeries(returns(X))
>
> # Spec = portfolioSpec(model = list(type = c("MV"),
> # estimator = c("mean", "cov"), tailRisk = list(), params = list()),
> # portfolio = list(weights = NULL, targetReturn = 0,
> # targetRisk = 0, targetAlpha = 0.05, riskFreeRate = NULL,
> # nFrontierPoints = 50),
> # solver = list(solver = c("quadprog"), trace = FALSE))
> Spec = portfolioSpec()
> frontier <- portfolioFrontier(R, Spec, c("minW[1:nAssets]=0"))
> # weightsSlider(frontier)
>
> ptf <-
> frontier at portfolio$weights[which.min(getTargetRisk(frontier)[,1])+1,]*100
> ptf
>
> assets2 <- c(
> "ENG.MI",
> "^SPMIB"
> )
>
> X2 <- cbind(eng.mi[1:(length(eng.mi)-1)], spmib[1:(length(spmib)-1)])
> colnames(X2) <- assets2
>
> R2 <- as.timeSeries(returns(X2))
> frontier <- portfolioFrontier(R2, Spec, c("minW[1:nAssets]=0"))
>
> ptf <-
> frontier at portfolio$weights[which.min(getTargetRisk(frontier)[,1])+1,]*100
> ptf
>
> -----------------------------
>
> The asset allocation (in Rmetrics):
>
>
> F.MI ENG.MI TIS.MI ^SPMIB
> 0.00000 24.30756 0.00000 75.69244
>
> ENG.MI ^SPMIB
> 24.48980 75.51020
>
>
>> cov(R)
>
> F.MI ENG.MI TIS.MI ^SPMIB
> F.MI 0.0029905040 0.0008974621 0.0010289887 0.0009954717
> ENG.MI 0.0008974621 0.0014935276 0.0004278133 0.0002809398
> TIS.MI 0.0010289887 0.0004278133 0.0052708621 0.0007186357
> ^SPMIB 0.0009954717 0.0002809398 0.0007186357 0.0005617209
>> cov(R2)
> ENG.MI ^SPMIB
> ENG.MI 0.0014197889 0.0002578205
> ^SPMIB 0.0002578205 0.0005791276
>
> I would think that if a weight is within epsilon of zero, then removing it
> from the computation should have minimal impact on the result.
>
>> eigen(cov(R))
> $values
> [1] 0.0060129474 0.0030233942 0.0010997423 0.0001805307
>
> $vectors
> [,1] [,2] [,3] [,4]
> [1,] -0.4145084 0.7702681 0.36304798 -0.32103879
> [2,] -0.1770771 0.3541481 -0.91735850 0.04094150
> [3,] -0.8700674 -0.4871272 -0.02330958 -0.07173836
> [4,] -0.1995222 0.2096978 0.16157418 0.94345721
>
>> eigen(cov(R2))
> $values
> [1] 0.0014925599 0.0005063566
>
> $vectors
> [,1] [,2]
> [1,] -0.9623985 0.2716415
> [2,] -0.2716415 -0.9623985
>
> The difference of the asset allocation is small. It is not so for
> portfolio.optim. I will investigate the difference between Rmetric and
> tseries, because in my context the solver is the same (quadprog).
>
> Maybe the measure of the risk used in Rmetrics is not the variance as used
> in tseries and it is less sensitive. In fact, the two asset allocations
> are
> different.
>
> I have short constraints and the weights don't change if I change the
> order
> of the assets.
>
>
> Thanks in advance,
> Alberto Santini
> --
> View this message in context:
> http://www.nabble.com/portfolio.optim-and-assets-with-weigth-equals-to-zero...-tp19315076p19315076.html
> Sent from the Rmetrics mailing list archive at Nabble.com.
>
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