Inverse of a covariance matrix (loop)

10 Ansichten (letzte 30 Tage)
Kevin van Berkel
Kevin van Berkel am 25 Apr. 2013
Hi all,
I am stuck to create a loop which yields inverse of covariance matrices.
Data description:
I have the returns of three risky assets: mkt, hml and mom, from nov 3, 1926 up to dec 31, 2012.
For each year (so starting from Nov 3, 1927)I want the inverse covariance matrix for the three risky assets.
The dates are described (thanks Andrei) by the following code:
d = [19261103; 20121231];
ddte = datenum(num2str(d),'yyyymmdd');
ndte = (ddte(1):ddte(2))';
t = weekday(ndte);
ndte = ndte(t ~= 1 & t ~= 7);
yourdata = [date,mkt,hml,mom];
[yy,mm,dd] = datevec(yourdata(:,1));
ymd = [yy,mm,dd];
im = mm == 11 & dd >= 3;
ii = strfind([~im(1),im(:)'],[0 1]);
So I am stuck what do I have to add to retrieve the inverse covariance matrices per year.
Hopefully someone can help me out.
Thanks!
I adjusted the code with cov in it, but it does not yield the desired results:
d = [19261103; 20121231];
ddte = datenum(num2str(d),'yyyymmdd');
ndte = (ddte(1):ddte(2))';
t = weekday(ndte);
ndte = ndte(t ~= 1 & t ~= 7);
yourdata = [date,mkt,hml,mom];
[yy,mm,dd] = datevec(yourdata(:,1));
ymd = [yy,mm,dd];
im = mm == 11 & dd >= 3;
ii = strfind([~im(1),im(:)'],[0 1]);
sb = zeros(numel(ndte),1);
sb(ii) = 1;
sbc = cumsum(sb);
t = sbc > 0 & sbc ~= max(sbc);
sbb = sbc(t);
sb1 = find(sb(t));
wdta = yourdata(t,:);
[r, c] = ndgrid(sbb,1:size(wdta,2)-1);
out1 = accumarray([r(:) c(:)],reshape(wdta(:,2:4),[],1),[],@cov);
out = [ymd(ii(1:end-1),:),out1] ;
What do I do wrong?

Akzeptierte Antwort

Andrei Bobrov
Andrei Bobrov am 25 Apr. 2013
Try this is code:
d = [19261103; 20121231];
ddte = datenum(num2str(d),'yyyymmdd');
ndte = (ddte(1):ddte(2))';
t = weekday(ndte);
ndte = ndte(t ~= 1 & t ~= 7);
yourdata = [ndte,mkt,hml,mom];
[yy,mm,dd] = datevec(yourdata(:,1));
ymd = [yy,mm,dd];
im = mm == 11 & dd >= 3;
ii = strfind([~im(1),im(:)'],[0 1]);
sb = zeros(size(yourdata,1),1);
sb(ii) = 1;
sbc = cumsum(sb);
t = sbc > 0 & sbc ~= max(sbc);
sb1 = diff(find([sb(t);1]));
wdta = yourdata(t,:);
s = size(wdta,2) - 1;
ydcell = mat2cell(wdta(:,2:end),sb1,s);
out = cellfun(@(x)cov(x)\eye(s),ydcell,'un',0);

Weitere Antworten (1)

Kevin van Berkel
Kevin van Berkel am 25 Apr. 2013
Andrei you are a legend. Works perfect, thank you very much!

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