Defining the probability of bank debtors’ default using financial solvency assessment models
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Author(s)Yana KuznichenkoLink to ORCID Index: https://orcid.org/0000-0003-0815-4939
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Mariia DykhaLink to ORCID Index: http://orcid.org/0000-0003-4405-9429
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Natalia PavlovaLink to ORCID Index: http://orcid.org/0000-0002-1572-4648
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Serhiy FrolovLink to ORCID Index: https://orcid.org/0000-0001-9374-7274
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Olha HryhorashLink to ORCID Index: https://orcid.org/0000-0002-8089-3755
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DOIhttp://dx.doi.org/10.21511/bbs.13(2).2018.01
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Article InfoVolume 13 2018, Issue #2, pp. 1-11
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277 Downloads
This work is licensed under a
Creative Commons Attribution-NonCommercial 4.0 International License
Due implementation of debtors’ financial solvency assessment models by Ukrainian banks with the aim of calculating the probability of their default (PD) is the next step towards the integration of Ukrainian banking system into global banking community, convergence of methodical approaches to assessing the credit risk with standards of international practice, possibility of using IRB-approach (an approach based on internal ratings) for calculating the regulatory requirements to capital adequacy.
The analysis of approaches to bank credit portfolio segmentation according to types of debtors and debtors’ financial solvency assessment models, depending on the performed segmentation and accumulated bank statistical data, from the point of view of its suitability for Ukrainian banks, will enable the banks to choose the most suitable ones for implementation taking into account nature and complexity of operations performed.
Such approaches will be more adapted to minimum capital requirements, simultaneously agreeing with national supervisory priorities.
- Keywords
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JEL Classification (Paper profile tab)G21, G32, G33
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References27
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Tables3
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Figures2
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- Figure 1. The main stages and the flow of determining the debtors’ PD coefficients
- Figure 2. Models used in international banking for assessing the debtors’ solvency
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- Table 1. Approaches to the bank’s loan portfolio segmentation
- Table 2. Assessing the model suitability for determining the rating/class of different segments of the bank’s loan portfolio
- Table 3. Models suitability for using by Ukrainian banks
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- Abdou, H., El-Masry, A., & Pointon, J. (2007). On the Applicability of Credit Scoring Models in Egyptian Banks. Banks and Bank Systems, 2(1), 4-20.
- Al-Shawabkeh, А., & Kanungo, R. (2017). Credit risk estimate using internal explicit knowledge. Investment Management and Financial Innovations, 14(1), 55- 66.
- Bank for International Settlements (2005). Basel II: International Convergence of Capital Measurement and Capital Standards: A Revised Framework.
- Bank for International Settlements (2015). Guidance on accounting for expected credit losses.
- Blanco-Oliver, A., Irimia- Dieguez, A., Oliver-Alfonso, M. D., & Vázquez-Cueto, M. J. (2016). Hybrid model using logit and nonparametric methods for predicting micro-entity failure. Investment Management and Financial Innovations, 13(3), 35-46.
- Borio, C. E. V. (2011). Rediscover¬ing the Macroeconomic Roots of Financial Stability Policy: Journey, Challenges, and a Way Forward. Annual Review of Financial Economics, 3, 87-117.
- Bunker, R., Naeem, A., & Zhang, W. (2016). Improving a Credit Scoring Model by Incorporating Bank Statement Derived.
- Deloitte (2016). Credit scoring Case study in data analytics.
- Dolinskyi, L. B. (2016). Моделювання ризику дефолтів банківських установ [Modeliuvannia ryzyku defoltiv bankivskykh ustanov].
- Edward, H. K. Ng (2012). Testing the consistency of internal credit ratings. Banks and Bank Systems, 7(3), 25-32.
- Genriha, I., & Voronova, I. (2012). Methods for Evaluating the Creditworthiness of Borrowers. Scientific Journal of RTU, 22, 42-49.
- Gurný, P., & Gurný, M. (2013). Comparison of the Credit Scoring Models on PD Estimation of US Banks. Prague economic papers, 2, 163-181.
- Karminskyi, A. M. (2012). Ймовірність дефолту банку і її моделювання [Imovirnist defoltu banku i yii modeliuvannia]. Finansova Analityka: Problemy i Rishennia, 41, 2-13.
- Kazanskyi, A. A. (2016). Функціонування внутрішньої рейтинго¬вої системи комерційного банку [Funktsionuvannia reitynhovoi systemy komertsiinoho banku]. Problemy Suchasnoi Ekonomiky, 9, 127-131.
- Kovalenko, V. V., & Nenad, D. O. (2017). Методи управління кредитним ризиком та їх місце в забезпеченні платоспроможності банків [Metody upravlinnia kredytnym ryzykom ta yikh mistse v zabezpechenni platospromozhnosti bankiv]. Hroshi, Finansy ta Kredyt, 3(08), 270-274.
- LigaZakon (2014). Про ратифікацію Угоди про асоціацію між Україною, з однієї сторони, та Європейським Союзом, Європейським співтовариством з атомної енергії і їхніми державами- членами, з іншої сторони: Закон України від 16.09.2014 №1678/ VII [Pro Ratyfikatsiiu Uhody mizh Ukrainoiu, z odniiei storony, ta Yevropeiskym Soiuzom, Yevropeiskym spivtovarystvom z atomnoi enerhii i yikhnimy derzhavamy-chlenamy, z inshoi storony: Zakon Ukrainy vid 16.09.2014 No. 1678/VII].
- LigaZakon (2018). Положення про визначення банками України розміру кредитного ризику за активними банківськими операціями: Постанова Правління Національного банку України від 30.06.2018 № 351 [Polozhennia pro vyznachennia bankamy Ukrainy rozmiru kredytnoho ryzyku za aktyvnymy bankivskymy operatsiiamy: Postanova Pravlinnia Natsionalnoho banku Ukrainy vid 30.06.2018 No. 351].
- Maarse, B. (2012). Backtesting Framework for PD, EAD and LGD (Master Thesis). (85 p.). Rabobank.
- National Bank of Ukraine (2018). Основні принципи ефективного банківського нагляду [Osnovni pryntsypy efektyvnoho bankivskoho nahliadu].
- National Securities and Stock Market Commission (2016). Регламент Європейського парламенту та Ради (ЄС) No. 575/2013 від 26.06.2013. Про пруденційні вимоги до кредитних організацій та інвестиційних компаній, що вносить зміни до Регламенту (ЄС) № 648/2012 [Rehlament Yevropeiskoho parlamentu ta Rady (YeS) No. 575/2013 vid 26.06.2013 Pro prudentsiini vymohy do kredytnykh orhanizatsii ta investytsiinykh kompanii, shcho vnosyt zminy do Rehlamentu (YeS) No. 648/2012].
- Shkodra, J., & Ismajli, H. (2017). Determinants of the credit risk in developing countries: a case of Kosovo banking sector. Banks and Bank Systems, 12(4), 90- 97.
- Sofronova, V. V. (2016). Оцінка дефолту боржника [Otsinka defoltu borzhnyka]. Finansova Analityka: Problemy i Rishennia, 3, 39-48.
- Stezhkin, A. A. (2015). Про методи валідації рейтингових систем в рамках підходу внутрішніх рейтингів до оцінки кредитного ризику банків [Pro metody validatsii reitynhovykh system v ramkakh pidkhodu vnutrishnikh reitynhiv do otsinky kredytnoho ryzyku bankiv]. Finansova Analityka: Problemy i Rishennia, 32, 29-41.
- Supervisory Statement (2013). Credit Risk: Internal Ratings Based Approaches (23 p.). Bank of England, Prudential Regulation Authority.
- Tasche, D. (2008). Validation of Internal Rating Systems and PD Estimates. In The Analytics of Risk Model Valuation (pp. 171-198). Elsevier.
- Tereshchenko, O. O. (2012). Оцінка кредитних ризиків: відповідність новацій НБУ міжнародній практиці [Otsinka kredytnykh ryzykiv: vidpovidnist novatsii NBU mizhnarodnii praktytsi]. Visnyk NBU, 9, 4-8.
- Wezel, T., Chan, Lau J. A., & Columba, F. (2012). Dynamic Loan Loss Provisioning Simulations on Effectiveness and Guide to Implementation. IMF Working Papers, 1(110), 8-11.
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Food and beverage stocks responding to COVID-19
Lai Cao Mai Phuong
doi: http://dx.doi.org/10.21511/imfi.18(3).2021.30
Investment Management and Financial Innovations Volume 18, 2021 Issue #3 pp. 359-371 Views: 982 Downloads: 819 TO CITE АНОТАЦІЯThis paper investigated how food and beverage (F&B) stocks react to COVID-19. The event study method was applied to four events including the first and second events, were the first COVID-19 positive patients detected in the largest and second-largest economic center of Vietnam. The third and fourth events are related to strong measures to prevent the spread of COVID-19: the nationwide lockdown at the beginning of the second quarter of 2020, and the lockdown of Danang at the beginning of the third quarter of 2020. The results show that the reaction of F&B stock prices to events supports the semi-strong form of efficient market theory. The strong and lasting negative reaction of F&B stocks to the first event can be explained by surprise (first case in Vietnam) and Hochiminh city’s economic engine driving role in the development of Vietnam’s economy. The study finds that heuristic decision-making from nationwide lockdowns (suppression of supply chains during lockdowns) can explain the sub-sector of farming-fishing-ranching products reacted more strongly to the lockdown event in Danang. Based on the research results, this paper provides some policy implications for managers and notes for securities investors.
