Prediction of commercial bank failure via multivariate statistical analysis of financial structures: The Turkish case

By Serpil Canbas, Altan Cabuk, S. Kiliç. European Journal of Operational Research, 2005

319 citations recorded by the source corpus.

Subfields: Accounting, Artificial Intelligence, Finance

View Paper: https://www.semanticscholar.org/paper/512525c9da48ef6e9e55ac2df318295d5971e6e7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

1. Iftekhar Hasan
2. Yuliya Demyanyk
3. Vadlamani Ravi
4. P. Ravi Kumar
5. Mingxing Liu
6. Qi Zhang
7. Victor C. Shih
8. Yong Tan

In Artificial Intelligence

1. Yuliya Demyanyk
2. Iftekhar Hasan
3. Vadlamani Ravi
4. P. Ravi Kumar
5. Mingxing Liu
6. Qi Zhang
7. Victor C. Shih
8. Arash Bahrammirzaee

In Finance

1. Yuliya Demyanyk
2. Vadlamani Ravi
3. P. Ravi Kumar
4. Iftekhar Hasan
5. Mingxing Liu
6. Qi Zhang
7. Victor C. Shih
8. Yong Tan

Citations in the corpus

• Financial Crises and Bank Failures: A Review of Prediction Methods (2010, methodology): “[51] propose an Integrated Early Warning System (IEWS) that combines DA, Logit, Probit, and Principal Component Analysis (PCA), which can help predict bank failure.”
• The effect of capital ratios on the risk, efficiency and profitability of banks: Evidence from OECD countries (2017, unknown): “These components are then used to examine which combination of capital ratios 13 To perform PCA, several criteria need to be met (Canbas et al., 2005; Shih et al., 2007).”
• Bank risk and performance in the MENA region: The importance of capital requirements (2016, unknown): “Another explanation is provided by Ghosh (2015): Banks demand higher interest margins in 18 To perform PCA, several steps need to be respected (Canbas et al., 2005; Shih et al., 2007; Klomp and de Haan, 2012).”
• Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review (2007, methodology): “[18] proposed an integrated early warning system (IEWS) by combining DA, logistic regression, pro-”
• Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey (2010, unknown): “In their seminal study, Charnes et al. (1978) proposed a model that had an input orientation and assumed CRS.”
• Comparing the performance of Chinese banks: A principal component approach ☆ (2007, methodology): “Our PCA approach closely follows researchers who want to gauge the relative health of banks rather than the relative efficiency of banks (Canbas et al., 2005).”