[R-SIG-Finance] Principal Component Analysis in Credit Risk
Josh-CH.Chien at nanshan.com.tw
Thu Sep 17 01:57:11 CEST 2015
Sound like you will find the "key" word as trigger for default or not default of company.
Based on your information, I think Daniel's response is right. You should focus on factor model.
However, in my understanding, PCA is a statistical method to tell us every part's explanation, but every party can't be given any meaning on economic view.
If it's you want, just type "PCA in r / PCA in r library" in google search.
You will found a lot library to deal with this issue and take time to check for choosing one of them you need.
Risk Analytics & Projects
Risk Management Dept.
Nan Shan Life Insurance Co.
Email: Josh-CH.Chien at NANSHAN.com.tw
From: R-SIG-Finance [mailto:r-sig-finance-bounces at r-project.org] On Behalf Of Amelia Marsh via R-SIG-Finance
Sent: Thursday, September 17, 2015 1:50 AM
To: r-sig-finance at r-project.org
Subject: [R-SIG-Finance] Principal Component Analysis in Credit Risk
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.
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