[R-SIG-Finance] BLCOP / Idzorek working paper

[Francisco Gochez]

Hi Heiko,

Thanks for bringing this to my attention.  I will look into the matter
over the weekend to see what might be wrong.  In reality,
"optimalPortfolios" is more or less a "toy" to experiment with, and not
meant to be used as a serious tool.  The next version of the package,
which will be out soon, will interface with some of Rmetric's portfolio
optimization tools.  I am in the process of discussing how best to do
this with Prof. Diethelm Wuertz at the moment.

Kind regards,

Francisco

mango solutions

S & R Consulting and Training

+44 (0)1249 767 700


-----Original Message-----
From: r-sig-finance-bounces at stat.math.ethz.ch
[mailto:r-sig-finance-bounces at stat.math.ethz.ch] On Behalf Of Heiko
Mayer
Sent: 15 May 2009 07:26
To: r-sig-finance at stat.math.ethz.ch
Subject: [R-SIG-Finance] BLCOP / Idzorek working paper

Hi all,

I have read the working paper from Idzorek regarding Black Litterman as
shown below. As the examples of the BLCOP manuals are based on that
paper, I have expected equal results. Posterior looks good (beside
bonds) , but the optimized portfolio weights (Idzorek: page 17, table 6)
are completly different. No bonds are allocated. Beside long only, I
cannot see any constraints, therefore I assume "solve.QP" used in
"optimalPortfolios" should work. Any ideas?
As markets tend to overreact significantly sometimes, it might not the
best idea using market cap. Would it be a good idea to start with risk
(sigma) adjusted weights and re-optimize these to get the prior returns?

library(BLCOP)
## example from Thomas M. Idzorek's paper "A STEP-BY-STEP GUIDE TO THE
BLACK-LITTERMAN MODEL"
#
http://corporate.morningstar.com/ib/documents/MethodologyDocuments/IBBAs
sociates/BlackLitterman.pdf
x <-
c(0.001005,0.001328,-0.000579,-0.000675,0.000121,0.000128,-0.000445,-0.0
00437 ,
0.001328,0.007277,-0.001307,-0.000610,-0.002237,-0.000989,0.001442,-0.00
1535 ,
-0.000579,-0.001307,0.059852,0.027588,0.063497,0.023036,0.032967,0.04803
9 ,
-0.000675,-0.000610,0.027588,0.029609,0.026572,0.021465,0.020697,0.02985
4 ,
0.000121,-0.002237,0.063497,0.026572,0.102488,0.042744,0.039943,0.065994
,
0.000128,-0.000989,0.023036,0.021465,0.042744,0.032056,0.019881,0.032235
,
-0.000445,0.001442,0.032967,0.020697,0.039943,0.019881,0.028355,0.035064
,
-0.000437,-0.001535,0.048039,0.029854,0.065994,0.032235,0.035064,0.07995
8 ) varCov <- matrix(x, ncol = 8, nrow = 8) mu <- c(0.08, 0.67,6.41,
4.08, 7.43, 3.70, 4.80, 6.60) / 100 pick <- matrix(0, ncol = 8, nrow =
3, dimnames = list(NULL, letters[1:8])) pick[1,7] <- 1 pick[2,1] <- -1;
pick[2,2] <- 1 pick[3, 3:6] <- c(0.9, -0.9, .1, -.1) confidences <- 1 /
c(0.000709, 0.000141, 0.000866) # Replaced wrong value "0.00709". Zero
was missing.
myViews <- BLViews(pick, c(0.0525, 0.0025, 0.02), confidences,
letters[1:8]) myPosterior <- posteriorEst(myViews, tau = 0.025, mu,
varCov )
optimalPortfolios(myPosterior)

Thanks,
Heiko
--

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