Browse > Article
http://dx.doi.org/10.13106/jafeb.2021.vol8.no1.573

Association of Financial Distress and Predicted Bankruptcy: The Case of Pakistani Banking Sector  

ULLAH, Hafeez (College of Management, Ocean University of China)
WANG, Zhuquan (College of Management, Ocean University of China)
ABBAS, Muhammad Ghazanfar (College of Management, Ocean University of China)
ZHANG, Fan (College of Management, Ocean University of China)
SHAHZAD, Umeair (College of Management, Ocean University of China)
MAHMOOD, Memon Rafait (College of Management, Ocean University of China)
Publication Information
The Journal of Asian Finance, Economics and Business / v.8, no.1, 2021 , pp. 573-585 More about this Journal
Abstract
The banking sector is one of the most important sectors in Pakistan's struggling economy. Recent studies have recommended that suitable methods can be applied to predict bankruptcy. In this context, this work analyzes Pakistan's banking sector's financial status through the five-factor Altman Z-score model, which determines the probability of bankruptcy for an organization. Banking data has been collected through the Pakistan Stock Exchange (PSX) in the period 2013-2017. The Z-score assessment criteria is defined as: Z> 2.99 - "safe" zone; Z> 1.8 Z>2.98- "grey" zone; and Z <1.8 - "distress" zone. Results show good predictions for the local banking industry, while most foreign Pakistani banks were found bankrupt with the Z-score below 1.1. One of the financial risks investors face when investing in any company is the risk of bankruptcy. One of the most used models for predicting financial distress for any company is Altman's Z-score model. On the other hand, the Z-score analysis suggests that all banking establishments are not bankrupt because they have sufficient ability to control bankruptcy. At the same time, foreign banks failed financially and would not be able to be sustained in the future because they do not have the ability to pay the short-term and long-term debt.
Keywords
Altman Z -Score Application; Five-Factors Analysis; Financial Distress; Bankruptcy; Banking Industry;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Hilston Keener, M. (2013). Predicting the financial failure of retail companies in the United States. Journal of Business & Economics Research, 11(8), 373-380. doi:10.19030/jber.v11i8.7982   DOI
2 Hoang Tien, N., Thuong, T. M., Minh Duc, L. D., & Hoang Yen, N. T. (2019). Enhancing independence of local auditing services by profiting from experiences of the Big4 group (KPMG, Deloitte, PWC E&Y) operating in the Vietnam market. Cogent Business & Management, 6(1). doi:10.1080/23311975.2019.1605702   DOI
3 Hult, H., Lindskog, F., Hammarlid, O., & Rehn, C. J. (2012). Risk and portfolio analysis. Springer Series in Operations Research and Financial Engineering. doi:10.1007/978-1-4614-4103-8   DOI
4 Husein, M. F., & Pambekti, G. T. (2015). The precision of the models of Altman, Springate, Zmijewski, and GROVER for predicting financial distress. Journal of Economics, Business & Accountancy Ventura, 17(3), 405-416. doi:10.14414/jebav.v17i3.362   DOI
5 Hwang, B., Zhao, X., & Gay, M. J. (2013). Public-private partnership projects in Singapore: Factors, critical risks, and preferred risk allocation from the contractors' perspective. International Journal of Project Management, 31(3), 424-433. doi:10.1016/j.ijproman.2012.08.003   DOI
6 Jackson, P., & Perraudin, W. (2000). Regulatory implications of credit risk modeling. Journal of Banking & Finance, 24(1-2), 1-14. doi:10.1016/s0378-4266(99)00050-3   DOI
7 Jennergren, L. P. (2013). Firm valuation with bankruptcy risk. Journal of Business Valuation and Economic Loss Analysis, 8(1), 41. doi:10.1515/jbvela-2013-0009   DOI
8 Kida, T. (1980). An investigation into auditors' continuity and related qualification judgments. Journal of Accounting Research, 18(2), 506-523. doi:10.2307/2490590   DOI
9 Kuo, Y., & Cheng, M. H. (2018). Budgeting and financial management of public infrastructure: The experience of Taiwan. Value for Money: Budget and financial management reform in the People's Republic of China, Taiwan, and Australia, 221-250. doi:10.22459/vm.01.2018.11   DOI
10 Kuruppu, N., Laswad, F., & Oyelere, P. (2003). The efficacy of liquidation and bankruptcy prediction models for assessing going concern. Managerial Auditing Journal, 18(6/7), 577-590. doi:10.1108/02686900310482713   DOI
11 Kusvanti, H., Suhendro, S., & Dewi, R. R. (2019). Individual factors that influence the ethical behavior of accounting students. eBA Journal: Journal Economics, Business, and Accounting, 5(1), 1-10. doi:10.32492/eba.v5i1.705   DOI
12 Kwak, W. (2014). Bankruptcy prediction using data mining tools. Encyclopedia of Business Analytics and Optimization, 220-226. doi:10.4018/978-1-4666-5202-6.ch021   DOI
13 Li, S., Miao, Y., Li, G., & Ikram, M. (2020). A novel varistructure grey forecasting model with speed adaptation and its application. Mathematics and Computers in Simulation, 172, 45-70. doi:10.1016/j.matcom.2019.12.020   DOI
14 Lin, C., & Wang, K. (2011). Predicting the bankruptcy risk of Taiwanese OTC corporations. Journal of Chinese Economic and Business Studies, 9(3), 301-316. doi:10.1080/14765284.2011.592359   DOI
15 Lin, K., & Dong, X. (2018). Corporate social responsibility engagement of financially distressed firms and their bankruptcy likelihood. Advances in Accounting, 43, 32-45. doi:10.1016/j.adiac.2018.08.001   DOI
16 MacDonald, S. (2007). Orange County bankruptcy. Encyclopedia of Public Administration and Public Policy, Second Edition (Print Version), 1377-1382. doi:10.1201/noe1420052756.ch279   DOI
17 Metcalfe, M. (1995). Bankruptcy forecasts. Forecasting Profit, 237-258. doi:10.1007/978-1-4615-2255-3_12   DOI
18 Mahmoudi, A., Bagherpour, M., & Javed, S. A. (2019). Grey earned value management: Theory and applications. IEEE Transactions on Engineering Management, 1-19. doi:10.1109/tem.2019.2920904   DOI
19 Malizia, E. E. (1975). Comparative evaluation of two sets of social indicators. Management Science, 22(3), 376-383. doi:10.1287/mnsc.22.3.376   DOI
20 Marini, F. (2013). Bankruptcy litigation and relationship banking. Journal of Business Finance & Accounting, 40(1-2), 272-284. doi:10.1111/jbfa.12011   DOI
21 Mizan, A. N., & Hossain, M. M. (2014). Financial soundness of cement industry of Bangladesh: An empirical investigation using Z-score. American Journal of Trade and Policy, 1(1), 16-22. doi:10.18034/ajtp.v1i1.357   DOI
22 Mubushar, M. (2020). The impact of CSR dimensions on customer participation behaviour in banking industry of Pakistan. International Journal of Psychosocial Rehabilitation, 24(4), 5815-5826. doi:10.37200/ijpr/v24i4/pr2020388   DOI
23 Muller, G. H., Steyn-Bruwer, B. W., & Hamman, W. D. (2009). Predicting financial distress of companies listed on the JSE: A comparison of techniques. South African Journal of Business Management, 40(1), 21-32. doi:10.4102/sajbm.v40i1.532   DOI
24 Nam, J., & Jinn, T. (2000). Bankruptcy prediction: Evidence from Korean listed companies during the IMF crisis. Journal of International Financial Management and Accounting, 11(3), 178-197. doi:10.1111/1467-646x.00061   DOI
25 Neumaier, J. (2014). Brustkrebs: Einfacher prognose-score. Im Focus Onkologie, 17(7-8), 26-26. doi:10.1007/s15015-014-1211-1   DOI
26 Al- Rawi, K., Kiani, R., & Vedd, R. R. (2011). The use of Altman equation for bankruptcy prediction in an industrial firm (Case study). International Business & Economics Research Journal, 7(7). doi:10.19030/iber.v7i7.3276   DOI
27 Abbas, Q., & Ahmad, A. R. (2011). Modeling bankruptcy prediction for non-financial firms: The case of Pakistan. SSRN Electronic Journal, 5(2), 26. doi:10.2139/ssrn.1917458   DOI
28 Agarwal, V., & Taffler, R. (2008). Does financial distress risk drive the momentum anomaly? Financial Management, 37(3), 461-484. doi:10.1111/j.1755-053x.2008.00021.x   DOI
29 Agarwal, V., & Taffler, R. (2008). Does financial distress risk drive the momentum anomaly? Financial Management, 37(3), 461-484. doi:10.1111/j.1755-053x.2008.00021.x   DOI
30 Alareeni, B. A., & Branson, J. (2012). Predicting listed companies' failure in Jordan using Altman models: A case study. International Journal of Business and Management, 8(1). doi:10.5539/ijbm.v8n1p113   DOI
31 Pang. (2013). Retail bankruptcy prediction. American Journal of Economics and Business Administration, 5(1), 29-46. doi:10.3844/ajebasp.2013.29.46   DOI
32 Nguyen-Phuoc, D. Q., De Gruyter, C., Nguyen, H. A., Nguyen, T., & Ngoc Su, D. (2020). Risky behaviours associated with traffic crashes among app-based motorcycle taxi drivers in Vietnam. Transportation Research Part F: Traffic Psychology and Behaviour, 70, 249-259. doi:10.1016/j.trf.2020.03.010   DOI
33 Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109-131. doi:10.2307/2490395   DOI
34 Othman, J., & Asutay, M. (2017). Integrated early warning prediction model for Islamic banks: The Malaysian case. Journal of Banking Regulation, 19(2), 118-130. doi:10.1057/s41261-017-0040-5   DOI
35 Pathan, S., & Faff, R. (2013). Does the board structure in banks affect their performance? Journal of Banking & Finance, 37(5), 1573-1589. doi:10.1016/j.jbankfin.2012.12.016   DOI
36 Pettit, P. H. (2012). 12. Voidable trusts. Equity and the Law of Trusts, 237-247. doi:10.1093/he/9780199694952.003.0012   DOI
37 Predicting the financial failure of retail companies in the United States. (2013). Journal of Business & Economics Research (JBER), 11(8), 373. doi:10.19030/jber.v11i8.7982   DOI
38 Rashid, A., & Shah, M. A. (2019). Do bank size and liquidity position matter in the monetary policy transmission mechanism? Evidence from Islamic and conventional banks in Pakistan. Journal of Islamic Business and Management, 9(2), 248-271. doi:10.26501/jibm/2019.0902-002   DOI
39 Alkhatib, K., & Eqab Al Bzour, A. (2011). Predicting corporate bankruptcy of Jordanian listed companies: Using Altman and Kida models. International Journal of Business and Management, 6(3). doi:10.5539/ijbm.v6n3p208   DOI
40 Alifiah, M. N., & Tahir, M. S. (2018). Predicting financial distress companies in the manufacturing and non-manufacturing sectors in Malaysia using macroeconomic variables. Management Science Letters, 593-604. doi:10.5267/j.msl.2018.4.031   DOI
41 Almamy, J., Aston, J., & Ngwa, L. N. (2016). An evaluation of Altman's Z-score using cash flow ratio to predict corporate failure amid the recent financial crisis: Evidence from the U.K. Journal of Corporate Finance, 36, 278-285. doi:10.1016/j.jcorpfin.2015.12.009   DOI
42 Altman, E. I. (1968). The prediction of corporate bankruptcy: A discriminant analysis. The Journal of Finance, 23(1), 193-194. doi:10.1111/j.1540-6261.1968.tb03007.x   DOI
43 Altman, E. I. (1984). The success of business failure prediction models. Journal of Banking & Finance, 8(2), 171-198. doi:10.1016/0378-4266(84)90003-7   DOI
44 Altman, E. I. (2000.). Predicting financial distress of companies: Revisiting the Z-score and ZETA® models. Handbook of Research Methods and Applications in Empirical Finance, 428-456. doi:10.4337/9780857936097.00027   DOI
45 Altman, E. I. (2018). Applications of distress prediction models: What have we learned after 50 years from the Z-score models? International Journal of Financial Studies, 6(3), 70. doi:10.3390/ijfs6030070   DOI
46 Altman, E. I., Haldeman, R. G., & Narayanan, P. (1977). ZETATM analysis a new model to identify the bankruptcy risk of corporations. Journal of Banking & Finance, 1(1), 29-54. doi:10.1016/0378-4266(77)90017-6   DOI
47 Siddiqui, S. A. (2012). Business bankruptcy prediction models: A significant study of Altman's Z-score model. SSRN Electronic Journal, 3(1), 212-219. doi:10.2139/ssrn.2128475   DOI
48 Restructuring out-of-Court and the cost of financial distress. (2019). Corporate Financial Distress, Restructuring, and Bankruptcy, 71-90. doi:10.1002/9781119541929.ch4   DOI
49 Serrano-Cinca, C., & Gutierrez-Nieto, B. (2013). A decision support system for financial and social investment. Applied Economics, 45(28), 4060-4070. doi:10.1080/00036846.2012.748180   DOI
50 Shahzad, U., Fukai, L., Mahmood, F., Jing, L., & Ahmad, Z. (2020). Reliable and advanced predictors for corporate financial choices in Pakistan. Journal of Asian Finance, Economics, and Business, 7(7), 73-84. doi:10.13106/jafeb.2020.vol7.no7.073   DOI
51 Slawsky, J., & Zafar, S. (2017). Developing and managing a successful payment cards business. London, UK: Routledge. doi:10.4324/9781315258065   DOI
52 Sofat, N. (2015). Latest approaches to the management of OA in humans. BMC Musculoskeletal Disorders, 16(S4). doi:10.1186/1471-2474-16-s1-s4   DOI
53 Taffler, R. J. (1983). The assessment of company solvency and performance using a statistical model. Accounting and Business Research, 13(52), 295-308. doi:10.1080/00014788.1983.9729767   DOI
54 Thakor, A. V. (2018). Post-crisis regulatory reform in banking: Address insolvency risk, not illiquidity! Journal of Financial Stability, 37, 107-111. doi:10.1016/j.jfs.2018.03.009   DOI
55 Tian, S., Yu, Y., & Guo, H. (2015). Variable selection and corporate bankruptcy forecasts. Journal of Banking & Finance, 52, 89-100. doi:10.1016/j.jbankfin.2014.12.003   DOI
56 Baginski, S. P., & Wahlen, J. M. (2003). Residual income risk, intrinsic values, and share prices. The Accounting Review, 78(1), 327-351. doi:10.2308/accr.2003.78.1.327   DOI
57 Altman, E. I., Hotchkiss, E., & Wang, W. (2019). Corporate financial distress, restructuring, and bankruptcy. New York, NY: Wiley. doi:10.1002/9781119541929   DOI
58 Altman, E. I., Kant, T., & Rattanaruengyot, T. (2009). Post-Chapter 11 bankruptcy performance: Avoiding Chapter 22. Journal of Applied Corporate Finance, 21(3), 53-64. doi:10.1111/j.1745-6622.2009.00239.x   DOI
59 Anser, M. K., Abbas, Q., Chaudhry, I. S., & Khan, A. (2020). Optimal oil stockpiling, peak oil, and general equilibrium: A case study of South Asia (oil importers) and Middle East (oil supplier). Environmental Science and Pollution Research, 27(16), 19304-19313. doi:10.1007/s11356-020-08419-7   DOI
60 Barboza, F., Kimura, H., & Altman, E. (2017). Machine learning models and bankruptcy prediction. Expert Systems with Applications, 83, 405-417. doi:10.1016/j.eswa.2017.04.006   DOI
61 Barniv, R. (1999). The value relevance of inflation-adjusted and historical-cost earnings during hyperinflation. Journal of International Accounting, Auditing, and Taxation, 8(2), 269-287. doi:10.1016/s1061-9518(99)00016-6   DOI
62 Altman, E. I., Hartzell, J., & Peck, M. (1998). Emerging market corporate bonds - a scoring system. The New York University Salomon Center Series on Financial Markets and Institutions, 391-400. doi:10.1007/978-1-4615-6197-2_25   DOI
63 Basu, S., Hwang, L., Mitsudome, T., & Weintrop, J. (2007). Corporate governance, top executive compensation, and firm performance in Japan. Pacific-Basin Finance Journal, 15(1), 56-79. doi:10.1016/j.pacfin.2006.05.002   DOI
64 White, M. J. (2007). Bankruptcy reform and credit cards. Journal of Economic Perspectives, 21(4), 175-199. doi:10.1257/jep.21.4.175   DOI
65 Van de Bunt, H., & Muller, T. (2017). The bankruptcy of the Dutch cannabis policy: Time for a restart. Contemporary Organized Crime, 11-23. doi:10.1007/978-3-319-55973-5_2   DOI
66 Verguet, S., Olson, Z. D., Babigumira, J. B., Desalegn, D., Johansson, K. A., Kruk, M. E., ... Jamison, D. T. (2015). Health gains and financial risk protection afforded by public financing of selected interventions in Ethiopia: An extended cost-effectiveness analysis. The Lancet Global Health, 3(5), 288-296. doi:10.1016/s2214-109x(14)70346-8   DOI
67 Wang, Z., Wang, Z., & Su, X. (2020). Are banks misled by leverage misestimate of Chinese listed companies? Nankai Business Review International, doi:10.1108/nbri-12-2019-0067   DOI
68 Wojcik-Mazur, A., & Szajt, M. (2015). Determinants of liquidity risk in commercial banks in the European Union. Argumenta Oeconomica, 2(35), 25-47. doi:10.15611/aoe.2015.2.02   DOI
69 Zafar, M. W., Zaidi, S. A., Sinha, A., Gedikli, A., & Hou, F. (2019). The role of stock market and banking sector development, and renewable energy consumption in carbon emissions: Insights from G-7 and N-11 countries. Resources Policy, 62, 427-436. doi:10.1016/j.resourpol.2019.05.003   DOI
70 Behn, D., & Langford, M. (2017). Trumping the environment? An empirical perspective on the legitimacy of investment treaty arbitration. The Journal of World Investment & Trade, 14-61. doi:10.1163/22119000-12340030   DOI
71 Behrens, G., & Neumaier, M. (2009). Change management of socially relevant habits. Management Review, 20(2), 176-189. doi:10.5771/0935-9915-2009-2-176   DOI
72 Bharath, S. T., & Shumway, T. (2008). Forecasting default with the Merton distance to default model. Review of Financial Studies, 21(3), 1339-1369. doi:10.1093/rfs/hhn044   DOI
73 Campello, M., Gao, J., Qiu, J., & Zhang, Y. (2017). Bankruptcy and the cost of organized labor: Evidence from union elections. The Review of Financial Studies, 31(3), 980-1013. doi:10.1093/rfs/hhx117   DOI
74 Campello, M., Gao, J., Qiu, J., & Zhang, Y. (2017). Bankruptcy and the cost of organized labor: Evidence from union elections. The Review of Financial Studies, 31(3), 980-1013. doi:10.1093/rfs/hhx117   DOI
75 Chadha, P. (2016). Exploring the financial performance of the listed companies in the Kuwait stock exchange using Altman's Z-score model. International Journal of Economics & Management Sciences, 5(3). doi:10.4172/2162-6359.1000341   DOI
76 Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 4, 71. doi:10.2307/2490171   DOI
77 Chandio, A. A., Jiang, Y., Rehman, A., Twumasi, M. A., Pathan, A. G., & Mohsin, M. (2020). Determinants of demand for credit by smallholder farmers': A farm-level analysis based on a survey in Sindh, Pakistan. Journal of Asian Business and Economic Studies, doi:10.1108/jabes-01-2020-0004   DOI
78 Curcio, D., De Simone, A., & Gallo, A. (2017). Financial crisis and international supervision: New evidence on the discretionary use of loan loss provisions at euro area commercial banks. The British Accounting Review, 49(2), 181-193. doi:10.1016/j.bar.2016.09.001   DOI
79 Choi, T., Wallace, S. W., & Wang, Y. (2016). Risk management and coordination in service supply chains: Information, logistics, and outsourcing. Journal of the Operational Research Society, 67(2), 159-164. doi:10.1057/jors.2015.115   DOI
80 Culp, P., Glennon, R., & Libecap, G. (2015). Conclusion. Shopping for Water, 31-31. doi:10.5822/978-1-61091-674-5_5   DOI
81 Dakovic, R., Czado, C., & Berg, D. (2010). Bankruptcy prediction in Norway: A comparison study. Applied Economics Letters, 17(17), 1739-1746. doi:10.1080/13504850903299594   DOI
82 Das, U., Oliva, M. A., & Tsuda, T. (2012). Sovereign risk: A macro-financial perspective. SSRN Electronic Journal. doi:10.2139/ssrn.2156044   DOI
83 Deakin, E. B. (1972). A discriminant analysis of predictors of business failure. Journal of Accounting Research, 10(1), 167. doi:10.2307/2490225   DOI
84 Chen, J. (2018). On exactitude in financial regulation: Valu-eat-Risk, expected shortfall, and expectiles. Risks, 6(2), 61. doi:10.3390/risks6020061   DOI
85 Deakin, M. A. (1972). Engineering mathematics in New Guinea. International Journal of Mathematical Education in Science and Technology, 3(3), 227-234. doi:10.1080/0020739700030303   DOI
86 Eba, H. (2017). Sieving for the primes to prove their infinitude. Missouri Journal of Mathematical Sciences, 29(2), 176-183. doi:10.35834/mjms/1513306829   DOI
87 Garrido, J., Bergthaler, W., DeLong, C., Johnson, J., Rasekh, A., Rosha, A., & Stetsenko, N. (2019). The use of data in assessing and designing insolvency systems. IMF Working Papers, 19(27), 1. doi:10.5089/9781484396223.001   DOI
88 Edelman, M. (2015). An unexpected path: Bankruptcy, justice, and intersecting identities in the Catholic sexual abuse scandals. Australian Feminist Law Journal, 41(2), 271-287. doi:10.1080/13200968.2015.1077550   DOI
89 Farn, J. (2016). Bankruptcy and bankruptcy proceedings in the United Arab Emirates. Global Insolvency and Bankruptcy Practice for Sustainable Economic Development, 175-232. doi:10.1057/9781137515759_6   DOI
90 Fijorek, K., & Grotowski, M. (2012). Bankruptcy prediction: Some results from a large sample of Polish companies. International Business Research, 5(9). doi:10.5539/ibr.v5n9p70   DOI
91 Graham, J. R. (2000). How big are the tax benefits of debt? The Journal of Finance, 55(5), 1901-1941. doi:10.1111/0022-1082.00277   DOI
92 Gruszczynski, M. (2019). Financial Microeconometrics. Berlin, Germany: Springer. doi:10.1007/978-3-030-34219-7_4   DOI
93 Ha, H. H., & Nguyen, H. (2020). Determinants of a voluntary audit of small and medium-sized enterprises: Evidence from Vietnam. Journal of Asian Finance, Economics, and Business, 7(5), 41-50. doi:10.13106/jafeb.2020.vol7.no5.041   DOI
94 Haq, M., Hu, D., Faff, R. W., & Pathan, S. (2016). New evidence on national culture and bank capital structure. Pacific-Basin Finance Journal, 50(C), 41-64.
95 Heaton, J. (2020). Predicting financial distress using Altman score, Grover score, springate score, zmijewski score (Case study on Consumer Goods Company). SSRN Electronic Journal, 8(1), 1-16. doi:10.2139/ssrn.3723802   DOI