[R-SIG-Finance] portfolio.optim and error in solve.QP: matrix D not positive definite
krishna
kriskumar at earthlink.net
Fri Jan 28 21:51:55 CET 2011
Also the link below might help with a large number of assets this is a
common problem.
https://stat.ethz.ch/pipermail/r-sig-finance/2008q3/002854.html
Cheers
Krishna
On Jan 27, 2011, at 12:03 PM, Guy Yollin <gyollin at r-programming.org>
wrote:
> Hi Lui,
>
> Without seeing the data this is just speculation but...
>
> Are you sure you want t(x)? If you're mixing up your observations
> versus your assets this may explain the error.
>
> The first parameter of portfolio.optim (in the tseries package) is a
> returns matrix, one column for each asset and one row for each day
> (assuming daily returns). If you have this wrong then for your
> small datasets you'd have more columns than rows and this could
> produce that error.
>
> Also, you don't have to pass the entire returns matrix to
> portfolio.optim, you could pass just the covariance matrix you
> calculate yourself and a vector (1-row matrix) of mean returns as
> follows:
>
>
> library(tseries)
> set.seed(2)
> R <- matrix(rnorm(100*10),nrow=100,ncol=10) # 10 assets, 100
> observations
> averet <- matrix(apply(R,2,mean),nrow=1)
> rcov <- cov(R)
> current_er <- 0.05
> (op <- portfolio.optim(x=averet,pm=current_er,covmat=rcov,riskless =
> FALSE,shorts = FALSE, rf = 0.0))
>
> Hope this helps.
>
> Best,
>
> Guy
>
>
> On 1/26/2011 7:51 PM, Lui ## wrote:
>> Dear Group,
>>
>> I have a large set of stocks and want to determine the efficient
>> frontier. The data set covers approx. 1.5 years and S&P 500 companies
>> (nothing weird). portfolio.optim from the PerformanceAnalytics
>> package
>> works very well and fast. However, whenever I decrease the number of
>> stocks in the portfolio (to 10 or 400), I receive an error message:
>>
>> "solve.QP(Dmat, dvec, Amat, bvec = b0, meq = 2) :
>> matrix D in quadratic function is not positive definite!"
>>
>> My command settings for portfolio.optim were:
>>
>> seed<- portfolio.optim(t(x), pm = current_er, riskless = FALSE,
>> shorts = FALSE, rf = 0.0)
>>
>> Even when I tried it with shorts = TRUE the error would still remain.
>> x is the set of stocks (stocks in columns, time in rows), current_er
>> is the target return (lies between the minimal mean and the maximum
>> mean of a long only portfolio).
>> I can not post the stock data here - so maybe you have some general
>> suggestions for me of what could have gone wrong... The covariance
>> matrix is positive definite. What could cause the problem? It works
>> fine with the large data set but does not work at all with the small
>> one...
>> Thanks a lot for your suggestions!
>>
>> Lui
>>
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>
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