[R-SIG-Finance] fPortfolio error
Attiglah, Mama
Mama_Attiglah at ssga.com
Fri Nov 14 15:58:25 CET 2008
Hi All,
I have been trying to use some of the Rmetrics packages to do some quick analysis but experiencing a pb of flexibility that I willl explain below by the package own example.
1)
# Data = as.timeSeries(data(smallcap.ts))
Data = Data[, c("BKE", "GG", "GYMB", "KRON")]
Data
Spec = portfolioSpec()
Spec
setTargetReturn(Spec) = mean(colMeans(Data))
Constraints = "LongOnly"
Ans = minvariancePortfolio(Data, Spec, Constraints)
In the optimisation, the historical mean and cov matrix
i.e
BKE GG GYMB KRON
0.02749712 0.02198486 0.01204526 0.03570639
and
BKE GG GYMB KRON
BKE 0.022526377 -0.003495562 0.010318065 0.007935904
GG -0.003495562 0.036070945 -0.003806943 -0.006872127
GYMB 0.010318065 -0.003806943 0.049574959 0.008098270
KRON 0.007935904 -0.006872127 0.008098270 0.028025520
are input.
1) My question is this: Is there anyway I can change any of those two inputs statistics computed from the historical data before feeding the optimizer, for instance if I have a different expectation of the future?
In order words, in case I don't have the historical data but do have the expected returns and covariance matrix, can I still ran the optimiser?
2) The target return set and the resulting portfolio returns coming from the optimal weights are different by 22 basis points. Is that due to the algorithm of solveRquadprog ?
mean
[1,] 0.02651604
> Spec
Portfolio Specification:
Portfolio Type: MV
Optimize: minRisk
Covariance Estimator: covEstimator
Target Return: 0.02430841
Portfolio Risk-Free Rate: 0
Number of Frontier Points: 50
Optimizer: solveRquadprog
Regards
-----
Mama Attiglah, PhD
Quantitative Research Analyst
Advanced Research Centre
State Street Bank
25 Bank Street, London E14 5NU
+44(0)20 7698 6290 (Direct Line)
+44 (0)207 004 2968 (Direct Fax)
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