A hybrid KMV model, random forests and rough set theory approach for credit rating

Knowledge-Based Systems

Volumn 33, Issue , 2012, Pages 166-172

  Yeh, Ching Chiang ^a   Lin, Fengyi ^b   Hsu, Chih Yu ^b  

^a NATIONAL TAIPEI UNIVERSITY OF BUSINESS   (Taiwan)

^b NATIONAL TAIPEI UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

Credit rating; Distance to default; KMV model; Random forests; Rough set theory

Indexed keywords

CLASSIFICATION RESULTS; CREDIT RATING PREDICTION; CREDIT RATINGS; DISTANCE TO DEFAULT; HISTORICAL INFORMATION; HYBRID MODEL; PREDICTIVE VARIABLES; RANDOM FORESTS;

COMMERCE; DECISION TREES; FORESTRY; INFORMATION USE; MATHEMATICAL MODELS; ROUGH SET THEORY;

RATING;

COMMERCE; DECISION THEORY; DISTANCE; INFORMATION RETRIEVAL; MATHEMATICAL MODELS; RANDOM PROCESSES; RATING;

EID: 84861589689     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2012.04.004     Document Type: Article

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