PMID- 30586437
OWN - NLM
STAT- MEDLINE
DCOM- 20190522
LR  - 20200309
IS  - 1932-6203 (Electronic)
IS  - 1932-6203 (Linking)
VI  - 13
IP  - 12
DP  - 2018
TI  - A novel financial risk assessment model for companies based on heterogeneous 
      information and aggregated historical data.
PG  - e0208166
LID - 10.1371/journal.pone.0208166 [doi]
LID - e0208166
AB  - 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.
FAU - Li, Dan-Ping
AU  - Li DP
AD  - School of Business, Hunan University of Science and Technology, Xiangtan, China.
FAU - Cheng, Si-Jie
AU  - Cheng SJ
AD  - School of Geosciences and Info-Physics, Central South University, Changsha, 
      China.
FAU - Cheng, Peng-Fei
AU  - Cheng PF
AUID- ORCID: 0000-0001-6121-1002
AD  - School of Business, Hunan University of Science and Technology, Xiangtan, China.
AD  - Hunan Engineering Research Center for Intelligent Decision Making and Big Data on 
      Industrial Development, Xiangtan, China.
FAU - Wang, Jian-Qiang
AU  - Wang JQ
AD  - Hunan Engineering Research Center for Intelligent Decision Making and Big Data on 
      Industrial Development, Xiangtan, China.
AD  - School of Business, Central South University, Changsha, China.
FAU - Zhang, Hong-Yu
AU  - Zhang HY
AD  - Hunan Engineering Research Center for Intelligent Decision Making and Big Data on 
      Industrial Development, Xiangtan, China.
AD  - School of Business, Central South University, Changsha, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20181226
PL  - United States
TA  - PLoS One
JT  - PloS one
JID - 101285081
SB  - IM
MH  - Commerce/economics/*organization & administration
MH  - Data Analysis
MH  - *Decision Making
MH  - *Decision Support Techniques
MH  - Financial Management/*methods
MH  - Fuzzy Logic
MH  - *Models, Economic
MH  - Risk Assessment/methods
PMC - PMC6306178
COIS- The authors have declared that no competing interests exist.
EDAT- 2018/12/27 06:00
MHDA- 2019/05/23 06:00
PMCR- 2018/12/26
CRDT- 2018/12/27 06:00
PHST- 2017/11/30 00:00 [received]
PHST- 2018/11/13 00:00 [accepted]
PHST- 2018/12/27 06:00 [entrez]
PHST- 2018/12/27 06:00 [pubmed]
PHST- 2019/05/23 06:00 [medline]
PHST- 2018/12/26 00:00 [pmc-release]
AID - PONE-D-17-42113 [pii]
AID - 10.1371/journal.pone.0208166 [doi]
PST - epublish
SO  - PLoS One. 2018 Dec 26;13(12):e0208166. doi: 10.1371/journal.pone.0208166. 
      eCollection 2018.