Code covered by the BSD License

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Matrix Decomposition

03 May 2011 (Updated 19 Nov 2012)

Positive definite correlation matrix based on spectral decomposition. Now both for .m, C and Mex

File Information
Description	Matrix decomposition using, e.g. the Cholesky decomposition requires the correlation matrix to be positive definite. That is, the eigenvalues must all be positive. In finance, this is rarely the case, and one often observes negative eigenvalues, or zero eigenvalues. These two functions do essentially the same thing. One adjusts only the <= 0 eigenvalues, while the other adjusts those eigenvalues, but then also increases the other non-negative eigenvalues to compensate for the higher 'weight' given to the smaller eigenvalues.
Required Products	Econometrics Toolbox Financial Toolbox Optimization Toolbox Statistics Toolbox MATLAB
MATLAB release	MATLAB 7.12 (R2011a)
Other requirements	The C programming code implementation is optimized for Intel 64-bit CPUs.

Tags for This File
Everyone's Tags	cholesky, cholesky decomposition, correlation matrix, decomposition, finance, mathematics, optimization, positive definite, semi positive definite, spectral decomposition(2), statistics
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Comments and Ratings (3)
18 Nov 2012	Aleksander	The latest submission includes the function written in the C programming language, as well as a MEX implementation, thus providing significant speed and memory enhancements.
03 Nov 2012	Aleksander	Does the trick!
07 Jul 2011	Marco	Very useful and efficient functions. Thanks to the willing and gentle author for the prompt and clear help.

Updates
20 Jul 2011	Removed one function
05 Nov 2012	Updated description
05 Nov 2012	Added screenshot
19 Nov 2012	This update includes the program in C programming code, as well as a MEX implementation, providing potentially significant speed and memory handling enhancements.