[R-SIG-Finance] Principal Component Analysis in Credit Risk

[Jason Curole]

Amelia,

In 2012 there was a piece in the magazine n+1 using factor analysis to
classify genre's of literature, which I think might be somewhat similar to
what you are trying to do (in your case genre being defaulted or not
defaulted). You can read about their work here:

https://nplusonemag.com/issue-13/essays/quantitative-formalism-an-experiment/

As I recall, they had pretty good success in classifying genres.  Hope this
helps.

Best, Jason

On Wed, Sep 16, 2015 at 12:50 PM, Amelia Marsh via R-SIG-Finance <
r-sig-finance at r-project.org> wrote:

> Dear Forum,
>
> I need some direction and guidance. This perhaps may sound a vague
> question, but I will try to be specific as far as possible.
>
> Recently I came to know about text analysis in R. Assuming I have analysts
> reports regarding say 250 companies. I am aware that out of these 25
> companies, 5 companies have defaulted. I have been asked to apply principal
> component analysis to each of these 25 companies to find out those words
> which if are occurring in say the 26th companies Analyst report, it will
> give me clear indication that this company will default.
>
> I understand this is really a vague question. To begin with, can Principal
> Component Analysis be used for text and if yes, can someone give me some
> direction or source.
>
> Regards
>
> Amelia
>
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