Probability of default as the early warning system for the Indonesian banking sector

Ari Christianti

Abstract


Early Warning System for banks is used to predict default risk. This research is to test the probability of defaults with the probability of default in the real condition of banks. The probability of default risk is measured by KMV-Merton Model and the probability of default in the real condition of banks is bank’s performance based on whether there are bank’s actions that cause changes in the bank's financial statements report. This study using banks listed in the Indonesian Stock Exchange (IDX) from 2010-2015. This study analysis probability of default with financial condition based from 4 commercial bank categories and BUKU (Commercial Bank Based on Business Activities) categories. The results of this study are the probability of default with Merton model give a strong signal against the default of bank for one bank only but for banks in BUKU 4 give a strong signal that banks in this category do not default. Since for other banks and for other BUKU categories do not represent the real condition from the probability of default. It can be concluded that the Merton model is not generated sufficient enough model to predict the probability of default since it assumes that the market is in under efficient condition, and it just considers firm-specific risk.

JEL Classification: G21, G32, G33

DOI: https://doi.org/10.26905/jkdp.v23i2.2856

 


Keywords


Banking sector; BUKU; KMV-Merton Model; Probability of default

Full Text:

PDF

References


Altman, E. I. (1968). Financial ratios, Discriminant Analysis, and the prediction of corporate bankruptcy. Journal of Finance, 23(4), 589-609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x

Acharya, V. V., Deniz, A., & Warburton, A. J. (2016). The end of market discipline? Investor expectations of implicit state guarantees. http://dx.doi.org/10.2139/ssrn.1961656

Bellalah, M., Zouari, S., & Levyne, O. (2016). The performance of hybrid models in the assessment of default risk. Economic Modelling, 52, 259–265. https://doi.org/10.1016/j.econmod.2014.10.051

Black, F, & Scholes, M. (1973). The pricing of options and corporate liabilities. The Journal of Political Economy, 81(3), 637-654. http://dx.doi.org/10.1086/260062

Camara, A., Popova, I., & Simkins, B. (2011). A comparative study of the probability of default for global financial firms. Journal of Banking and Finance, 36, 717-732. https://doi.org/10.1016/j.jbankfin.2011.02.019

Das, S. R., Hanouna, P., & Sarin, A. (2009). Accounting-based versus market-based cross-sectional models of CDS spreads. Journal of Banking and Finance, 33, 719–730. https://doi.org/10.1016/j.jbankfin.2008.11.003

Duan, J., & Ren, S. (2011). Assessing the default risk of chinese public companies in the energy industry. Thesis. Master Programme. Lunds University, Swedish.

Helen, D. (2015). Kinerja Semester I/2015: Laba Bank of India Indonesia Terkoreksi 20,11%. Retrieved from: https://finansial.bisnis.com/read/20150807/90/460334/kinerja-semester-i2015-laba-bank-of-india-indonesia-terkoreksi-2011.

Li, M.-Y. L., & Miu, P. (2010). A hybrid bankruptcy prediction model with dynamic loadings on accounting-ratio-based and market-based information: A binary quantile regression approach. Journal of Empirical Finance, 17(4), 818–833. https://doi.org/10.1016/j.jempfin.2010.04.004

Jones, S., Johnstone, D., & Roy Wilson. (2015). An empirical evaluation of the performance of binary classifiers in the prediction of credit ratings changes. Journal of Banking and Finance, 56, 72–85. https://doi.org/10.1016/j.jbankfin.2015.02.006

Jones, S., Johnstone, D., & Wilson, R. (2017). Predicting corporate bankruptcy: An evaluation of alternative statistical frameworks. Journal of Business Finance and Accounting, 44(1-2), 3–34. https://doi.org/10.1111/jbfa.12218

Jorion, P. (2009). Financial Risk Manager Handbook. 5th Edition. Published by John Wiley and Sons, Inc.

Kleinert, M. K. (2014). Comparison of bankruptcy prediction models of Altman (1969), Ohlson (1980) and Zmijewski (1984) on German and Belgian listed companies between 2008–2013. Thesis. Master Programme. University of Twente, Netherlands

Liang, X. (2012). An empirical estimation of the default risk of chinese listed company based on the Merton-KMV Model. Thesis. Norwegian School of Economics

Löffler, G., Posch, P. N. (2011). Credit Risk Modelling using Excel and VBA. Published by John Wiley & Sons Inc.

Majumder, D. (2006). Inefficient markets and credit risk modeling: Why Merton’s Model failed. Journal of Policy Modeling, 28(3), 307-318. https://doi.org/10.1016/j.jpolmod.2005.10.006

Mansi, S. A., Maxwell, W. F., & Zhang, A. (2012). Bankruptcy prediction models and the cost of debt. The Journal of Fixed Income 21(4), 25–42. https://doi.org/10.3905/jfi.2012.21.4.025

Mas Sari, S. (2014). Dikuasi Hary Tanoe, ICB Bumiputera resmi menjadi Bank MNC. Retrieved from: http://finansial.bisnis.com/read/20141025/90/267758/dikuasai-hary-tanoe-icb-bumiputera-resmi-menjadi-bank-mnc. October 25, 2014.

Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates, Journal of Finance, 29(2), 449-470. https://doi.org/10.1111/j.1540-6261.1974.tb03058.x

Nurfuadah, R. N. (2011). Fitch naikkan peringkat BTN ke 'AA(idn)'. Retrieved from: https://economy.okezone.com/read/2011/10/27/278/521125/fitch-naikkan-peringkat-btn-ke-aa-idn. October 27, 2011

Ohlson, J. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109-131. https://doi.org/10.2307/2490395

Rim, E. K., & Roy, A B. (2014). Classifying manufacturing firms in Lebanon: An application of Altman’s model. Procedia-Social and Behavioral Sciences, 109, 11–18. https://doi.org/10.1016/j.sbspro.2013.12.413

Sun, J., Li, H., Huang, Q-H., & He, K-Y. (2014). Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches. Knowledge-Based Systems, 57, 41–56 https://doi.org/10.1016/j.knosys.2013.12.006

Tanthanongsakkun, S., Pitt, D., & Treepongkaruna, S. (2009). A Comparison of corporate bankruptcy models in Australia: the Merton vs Accounting-based models. Asia-Pacific Journal of Risk And Insurance, 3, 93-112. https://doi.org/10.2202/2153-3792.1042

Tsesmelidakis, Z. & Merton, R. C. (2013). The value of implicit guarantees. Working Paper. MIT Working

Wu, Y., Gaunt, C., & Gray, S. F. (2010). A comparison of alternative bankruptcy prediction models. Journal of Contemporary Accounting and Economics, 6, 34–45 https://doi.org/10.1016/j.jcae.2010.04.002

Yeh, C.-C., Lin, F., & Hsu, C.-Y. (2012). A hybrid KMV model, random forests and rough set theory approach for credit rating. Knowledge-Based Systems, 33, 166–172. https://doi.org/10.1016/j.knosys.2012.04.004

Yusof, N. M., & Jaffar, M. M (2017). KMV-Merton Model-Based forecasting of default probabilities: A case study of Malaysian Airline System Berhad. Journal of Engineering and Applied Sciences, 12, 4297-4300.

Zmijewski, M. E. (1984). Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research, 22, 59-82. http://dx.doi.org/10.2307/2490859




DOI: https://doi.org/10.26905/jkdp.v23i2.2856

Refbacks

  • There are currently no refbacks.




Jurnal Keuangan dan Perbankan (Journal of Finance and Banking)

Diploma Program of Banking and Finance, Faculty of Economics and Business, University of Merdeka Malang

Published by University of Merdeka Malang

Mailing Address:
2nd floor Finance and Banking Building, Jl. Terusan Raya Dieng No. 57 Malang, East Java, Indonesia
Phone: -
Email: [email protected]

This work is licensed under a Creative
Commons Attribution-ShareAlike 4.0