One way to deal with variables of different nature/units is to scale
them with their standard deviations.
On 04/23/2014 10:53 AM, Adam Ginensky wrote:
I'm looking at clustering of stocks based on their fundamental
financial
data. I have about 80 variables per stock. I have the standard
k-means
package. Firstly, I am wondering if there are any other R packages
that
may be more useful for clustering of financial data.
My second, and more important (to me), question is- Should one scale
the
data before clustering. I'm particularly worried that since certain
variables can be orders of magnitude larger than other equally
interesting
variables (-think market cap and p/e). I realize this is not an R
question
per se, but I feel I am more likely to get a good answer out of this
forum
than any other because of the concentration of financial practitioners.
Of
course, I apologize in advance, if it is too 'off-topic' and then
simply
ask for a better place to post. Thanks.
Adam Ginensky
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