Study on credit risk of real estate industry based on genetic algorithm KMV model

This paper firstly analyzes the current situation of credit risk in China's real estate industry, and then compares the traditional and modern credit risk measurement models. On this basis, the KMV model is selected and the artificial intelligence model genetic algorithm (GA) is introduced to i...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 1629; no. 1; pp. 12072 - 12079
Main Authors Cheng, Xusheng, Sun, Ziran, Bao, Weiqi
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.09.2020
Subjects
Artificial intelligence
Credit risk
Economic development
Economic models
Empirical analysis
Genetic algorithms
Model accuracy
Physics
Real estate
Risk
China
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Summary:This paper firstly analyzes the current situation of credit risk in China's real estate industry, and then compares the traditional and modern credit risk measurement models. On this basis, the KMV model is selected and the artificial intelligence model genetic algorithm (GA) is introduced to improve the accuracy of KMV model. Secondly, annual financial data and stock trading data of 108 real estate listed companies from 2010 to 2019 are selected for empirical research. The analysis of the total default distance between the 108 companies and the actual economic development in China proves that the results of the GA-KMV model are in good agreement with the economic development trend, indicating that the model has good applicability. Finally, some suggestions are put forward according to the empirical results.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1629/1/012072