Dimensions of matrices being concatenated are not consistent.
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Hi, im having trouble in running a programm for the following reason: Dimensions of matrices being concatenated are not consistent.
vector names correspond to the forecast error decomposition of variance, as mentioned in %P=chol(Omega); Choleski factorization
However vectors have the same number of columns:
Y=data;
% will print results to the MATLAB command window
% set flag for Sim's correction factor
sims = 1;
maxlag = 12;
minlag = 1;
lrratio(Y,maxlag,minlag,sims);
%
T=length(Y);
NAR=1;
M=50;
H=12;
%
N=size(Y,2);
results=fvar(Y,NAR);
MPHI=mphi(results,NAR,N);
%matrix of variances y covariances
for i = 1:N
err(:,i) = results(i).resid;
end
Omega = err'*err/rows(err);
%P=chol(Omega); Choleski factorization
P=eye(N);
vnames = ['UNICREDIT ',
'CREDIT SUISSE ',
'SANTANDER ',
'UBS ',
'ING ',
'DEUTSCHE BANK ',
'HSBC ',
'SOCIETE GENERALE ',
'CREDIT AGRICOLE ',
'BNP PARIBAS ',
'BARCLAYS '];
vnames1 = ['unicredit ',
'credit suisse ',
'santander ',
'ubs ',
'ing ',
'deutsche bank ',
'hsbc ',
'societe generale ',
'credit agricole ',
'bnp paribas ',
'barclays '];
names={'UNICREDIT ' 'CREDIT SUISSE ' 'SANTANDER ' 'UBS ' 'ING ' 'DEUTSCHE BANK ' 'HSBC ' 'SOCIETE GENERALE ' 'CREDIT AGRICOLE ' 'BNP ' 'BARCLAYS '};
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