Assessing the Bankruptcy Risks of China's Emerging Port Industries: Modeling and Early Warning
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DOI: https://doi.org/10.15826/vestnik.2024.23.3.031
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- Bouvatier, Vincent & Lepetit, Laetitia & Rehault, Pierre-Nicolas & Strobel, Frank, 2023.
"Time-varying Z-score measures for bank insolvency risk: Best practice,"
Journal of Empirical Finance, Elsevier, vol. 73(C), pages 170-179.
- Vincent Bouvatier & Laetitia Lepetit & Pierre-Nicolas Rehault & Frank Strobel, 2023. "Time-varying Z-score measures for bank insolvency risk: Best practice," Post-Print hal-04285763, HAL.
- Lepetit, Laetitia & Strobel, Frank, 2015.
"Bank insolvency risk and Z-score measures: A refinement,"
Finance Research Letters, Elsevier, vol. 13(C), pages 214-224.
- Laetitia Lepetit & Frank Strobel, 2015. "Bank Insolvency Risk and Z-Score Measures: A Refinement," Post-Print hal-01204881, HAL.
- Zhu, Weidong & Zhang, Tianjiao & Wu, Yong & Li, Shaorong & Li, Zhimin, 2022. "Research on optimization of an enterprise financial risk early warning method based on the DS-RF model," International Review of Financial Analysis, Elsevier, vol. 81(C).
- Zhu, Ruihua & Chen, Fang, 2024. "Tax and financial credit risks—Empirical evidence from Chinese investment enterprises," Finance Research Letters, Elsevier, vol. 61(C).
- Rahman, Md Jahidur & Zhu, Hongtao, 2024. "Predicting financial distress using machine learning approaches: Evidence China," Journal of Contemporary Accounting and Economics, Elsevier, vol. 20(1).
- Afshan, Sahar & Leong, Ken Yien & Najmi, Arsalan & Razi, Ummara & Lelchumanan, Bawani & Cheong, Calvin Wing Hoh, 2024. "Fintech advancements for financial resilience: Analysing exchange rates and digital currencies during oil and financial risk," Resources Policy, Elsevier, vol. 88(C).
- Ouyang, Zi-sheng & Yang, Xi-te & Lai, Yongzeng, 2021. "Systemic financial risk early warning of financial market in China using Attention-LSTM model," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
- Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
- López Prol, Javier & Paul, Arijit, 2024. "Profitability landscapes for competitive photovoltaic self-consumption," Energy Policy, Elsevier, vol. 188(C).
- Tian, Sihua & Li, Shaofang & Gu, Qinen, 2023. "Measurement and contagion modelling of systemic risk in China's financial sectors: Evidence for functional data analysis and complex network," International Review of Financial Analysis, Elsevier, vol. 90(C).
- Allaj, Erindi & Sanfelici, Simona, 2023. "Early Warning Systems for identifying financial instability," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1777-1803.
- Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
- Chiaramonte, Laura & Croci, Ettore & Poli, Federica, 2015. "Should we trust the Z-score? Evidence from the European Banking Industry," Global Finance Journal, Elsevier, vol. 28(C), pages 111-131.
- Yu, Haiyan & Su, Tao, 2024. "ESG performance and corporate solvency," Finance Research Letters, Elsevier, vol. 59(C).
- Tarkocin, Coskun & Donduran, Murat, 2024. "Constructing early warning indicators for banks using machine learning models," The North American Journal of Economics and Finance, Elsevier, vol. 69(PB).
- Tang, Pan & Tang, Tiantian & Lu, Chennuo, 2024. "Predicting systemic financial risk with interpretable machine learning," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
- Kandpal, Bakul & Backe, Stian & Crespo del Granado, Pedro, 2024. "Power purchase agreements for plus energy neighbourhoods: Financial risk mitigation through predictive modelling and bargaining theory," Applied Energy, Elsevier, vol. 358(C).
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More about this item
Keywords
port emerging industry; financial early warning model; Y-score model; F-score model; Delphi method; Analytic Hierarchy Process method;All these keywords.
JEL classification:
- G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
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