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December 11th, 2012, 04:24 AM   #1
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Time Series Independent Component Analysis

I am trying to figure out how to do independent component analysis on a single stream of time series data (stock prices). The ica algorithm comes as part of the it++ package however it is necessary to perform some preprocessing on the time series data as ica works on the premise that the number of observations is at least as large as the number of sources.
The preprocessing involves constructing a matrix Y that contains the original time series in the 1st column, a lag-1 shifted version of the time series in the 2nd column etc.
eg.
Y= 1.0135518 - 0.7113242 - 0.3906069 1.565203
- 0.7113242 - 0.3906069 1.565203 0.0439317
- 0.3906069 1.565203 0.0439317 - 1.1656093
etc.

My questions are:
What steps are necessary to recover the independent sources after ICA is performed?
How to order the IC's from most significant to least significant.
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December 11th, 2012, 04:31 AM   #2
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Re: Time Series Independent Component Analysis

I have deleted the duplicate postings of this topic. This removes redundancy and prevents duplication of effort on the part of our contributors.
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