Financial Time Series Object Performance

Hello,
I am trying to use the Financial Time Series Object, because the utility functions that come with it look neat. However the object creation seems to be very slow.
Below is my code-snippet to create the object. Unfortunately my date data is not in one of the accepted formats so I have to read the data first with csvread then create the fints object.
rawdata = csvread(fullPathFilename,1);
fts = fints(datenum(num2str(rawdata(:,1)),'yyyymmdd'),rawdata(:,2:12), {'Open','High','Low','Close','UnadjustedClose','Cash','Volume','OpenInterest','TotalVolume','TotalOpenInterest','UnadjustedVolume'});
This is taking 10 times slower than simply reading the data into matrices with csvread (I am loading around 2000 stocks). Maybe it is due to date conversion, I don't know. How can I speed it up? What other performance bottlenecks are there in fints related functions?
Should I stick to matrices, instead?
Thanks

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Diese Frage ist geschlossen.

Gefragt:

am 16 Mär. 2013

Geschlossen:

am 20 Aug. 2021

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