correlation and covariance matrix construction
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hgeorgako
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- MadMax
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correlation and covariance matrix construction
Lets say you have 1-year daily data (250 data points) for each name, that's 250*85=21250 data points. That's only 21250/85= 5.8 data points per parameter.
The number of data points increase linearly in the number of names, however the number of parameters grows as 2x^2+x in the number of names.
positive definite matrix
The number of data points increase linearly in the number of names, however the number of parameters grows as 2x^2+x in the number of names.
positive definite matrix
- MadMax
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correlation and covariance matrix construction
hgeorgako,
how about
1- you build up that matrix on moving windows and show them how that matrix is moving around and see if they find any sense in that.
2- construct positions that will look riskless according to that matrix.
how about
1- you build up that matrix on moving windows and show them how that matrix is moving around and see if they find any sense in that.
2- construct positions that will look riskless according to that matrix.
- rakato
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correlation and covariance matrix construction
so how many data points per parameter do you think is sufficient?
The Feynman Problem-Solving Algorithm: (1) write down the problem; (2) think very hard; (3) write down the answer.
- Chuck
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correlation and covariance matrix construction
Can someone please tell me where I went wrong? I used Aaron's methodology...
[url=/User%20Files/1540/CORREL%20MATRIX1.xls]Attached File: CORREL MATRIX1.xls[/url]
[url=/User%20Files/1540/CORREL%20MATRIX1.xls]Attached File: CORREL MATRIX1.xls[/url]
Speculator
- Tradenator
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correlation and covariance matrix construction
I changed your returns from Ln(P2/P1) to P2/P1-1, and removed the 1 day lead. In Aaron's covariance matrix you need to divide by the number of rows. Finally, I removed the *100 you had going from the covariance to correlation. It's also a good idea to check against CORREL() and COVAR() so I did that too. Some of this is just for my calculation preferences, but the division by the sample size in the covariance matrix is important.
[url=/User%20Files/1915/CORREL%20MATRIX1.xls]Attached File: CORREL MATRIX1.xls[/url]
[url=/User%20Files/1915/CORREL%20MATRIX1.xls]Attached File: CORREL MATRIX1.xls[/url]
- Chuck
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- Joined: Thu Jan 01, 2004 12:00 am
correlation and covariance matrix construction
Thanks dood! I've always used 'Tools > Data Analysis > Correl > highlight returns' to get the matrix, but seeing how it is actually done using formulas/functions is really helpful. And I forgot to include count(column)...
I'm not doubting you, but why did you use beginning/ending-1 ? It gives me negative returns on up days.
I'm not doubting you, but why did you use beginning/ending-1 ? It gives me negative returns on up days.
Speculator
- urnash
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correlation and covariance matrix construction
It seems as if there are some tiny mistakes in the matrix named covaraiance using COVAR(). E.g. cells S33, T33, U33, V33 and W33 seems wrong. EDIT: It certainly seems like a nice useful sheet!
mattcushman: happiness levels are a I(0) process, not I(1).
- Tradenator
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correlation and covariance matrix construction
beginning/ending-1
that would be a vertical copulation Blush
that would be a vertical copulation Blush
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Jenian
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correlation and covariance matrix construction
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