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Bank Failure Prediction Models for the Developing and Developed Countries: Identifying the Economic Value Added for Predicting Failure

Author

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  • Yi-Shu Wang
  • Xue Jiang
  • Zhen-Jia Liu

Abstract

This study used data from 2003-2013, and used a logistic model to analyze the factors that influence financial early warning systems in developing and developed countries. We employed a bank capital adequacy ratio less than 8%, Tier I capital ratio less than 4%, and nonperforming loan ratio more than one third to measure bank failure and identify the financial ratio that most accurately predicts bank failure. The results indicate that the economic value added index is more effective than other indexes in predicting bank failure in NAFTA, ASEAN, EU, NIC, and G20 nations.

Suggested Citation

  • Yi-Shu Wang & Xue Jiang & Zhen-Jia Liu, 2016. "Bank Failure Prediction Models for the Developing and Developed Countries: Identifying the Economic Value Added for Predicting Failure," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 6(9), pages 522-533.
  • Handle: RePEc:asi:aeafrj:v:6:y:2016:i:9:p:522-533:id:1503
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    Citations

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    Cited by:

    1. Maria Bondarenko & Maria Semenova, 2018. "Do High Deposit Interest Rates Signal Bank Default? Evidence from the Russian Retail Deposit Market," HSE Working papers WP BRP 65/FE/2018, National Research University Higher School of Economics.
    2. Ashita Agrawal & Pitabas Mohanty & Navindra Kumar Totala, 2019. "Does EVA Beat ROA and ROE in Explaining the Stock Returns in Indian Scenario? An Evidence Using Mixed Effects Panel Data Regression Model," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 44(2), pages 103-134, May.
    3. Wang, Bo & Liu, Jinping & Alassafi, Madini O. & Alsaadi, Fawaz E. & Jahanshahi, Hadi & Bekiros, Stelios, 2022. "Intelligent parameter identification and prediction of variable time fractional derivative and application in a symmetric chaotic financial system," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).

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