A novel financial risk assessment model for companies based on heterogeneous information and aggregated historical data

Dan-Ping Li, Si-Jie Cheng, Peng-Fei Cheng, Jian-Qiang Wang and Hong-Yu Zhang

PLOS ONE, 2018, vol. 13, issue 12, 1-25

Abstract: The financial risk not only affects the development of the company itself, but also affects the economic development of the whole society; therefore, the financial risk assessment of company is an important part. At present, numerous methods of financial risk assessment have been researched by scholars. However, most of the extant methods neither integrated fuzzy sets with quantitative analysis, nor took into account the historical data of the past few years. To settle these defects, this paper proposes a novel financial risk assessment model for companies based on heterogeneous multiple-criteria decision-making (MCDM) and historical data. Subjective and objective indexes are comprehensively taken into consideration in the financial risk assessment index system of the model, which combines fuzzy theory with quantitative data analysis. Moreover, the assessment information obtained from historical financial information of company, credit rating agency and decision makers, including crisp numbers, triangular fuzzy numbers and neutrosophic numbers. Furthermore, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to determine the ranking order of companies according to their financial risk. Finally, an empirical study of financial risk assessment for companies is conducted, and the results of comparative analysis and sensitivity analysis suggest that the proposed model can effectively and reliably obtain the company with the lowest financial risk.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0208166

DOI: 10.1371/journal.pone.0208166

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