Credit Rating and Assignment of Naics Codes Using Lsi Method

The objective here is first, to improve automatic assignment of industry codes using LSI (lexical processing) by increasing the algorithm efficiency (both computationally and in term of input requirements), then quantify the lender's risk as "distance to default" (higher distance to default indicates default is less likely to occur), estimate the distance to default for each company and combine the results to obtain an estimate of the distance to default for each NAICS code.

Name thesis:degree_name

Master of Science in Mathematics (M.S.)

Level thesis:degree_level

Thesis (open access)

Discipline thesis:degree_discipline

Department of Mathematical Sciences

Year dc:date.available

2011

Author dc:creator

• Ouedraogo, Jerome

Contributors dc:contributor

• Charles Champ
• John Barkoulas

• ETD. LSI
• NAICS code
• Distance to default

Repository record dc:identifier

https://digitalcommons.georgiasouthern.edu/etd/671

OAI identifier oai:identifier

oai:digitalcommons.georgiasouthern.edu:etd-1671