International Journal of Financial Management

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Financial Distress and Bank Performance:A Study of Select Indian Banks


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1 MCM DAV College, Chandigarh, India
     

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Financial distress is technically used to evaluate the financial status of the firms in terms of insolvency and bankruptcy. In view of the rising corporate scams such as Enron, Parmalat, Satyam, Punjab and Sind bank, etc., it is imperative to predict financial distress as the fallout of bankruptcy causes heavy losses to the companies and thus affects the national economy. In particular, the banking sector plays a vital role in the economic development of a country. The main purpose of this study is to assess the financial performance of the banking sector in India using Altman (1968) Z-score model for the period 2012-2017. Z-score has been used as a tool to evaluate the credibility of the banks by estimating the Z-score values of the select banks in India. This value is useful when these banks demand loans from the RBI or any other funding agency. Thereafter, the effect of financial distress on the performance of banks has also been assessed by taking Tobin’s Q as the performance measure. The results revealed that distressed stocks outperform non-distressed stocks during the market upturns.

Keywords

Financial Distress, Banking Sector, Tobin’s Q.
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  • Aesen, M. R. (2011). Applying Altman’s Z-score to the financial crisis. Norwegian School of Economics. Retrieved from https://brage.bibsys.no/xmlui/bitstream/ handle/11250/169347/Aasen%202011.pdf?sequence=1

  • Agarwal, V., & Taffler, R. J. (2002). The distress factor hypothesis in equity returns: Market mispricing or omitted variable? Working Paper, Cranfield School of Management. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download? doi=10.1.1.195. 2420 &rep=rep1&type=pdf. Accessed on July 18, 2016.

  • Agarwal, V., & Taffler, R. J. (2007). Twenty-five years of the Taffler Z-score model: Does it really have predictive ability?. Journal of Accounting and Business Research, 37(4), 285-300.

  • Alexakis, P. (2008). Altman Z-score model and prediction of business failures. International Journal of Monetary Economics and Finance, 1(4), 329-337.

  • Alkhatib, K., & Bzour, A. E. A. (2011). Predicting corporate bankruptcy of Jordanian listed companies: Using Altman and Kida models. International Journal of Business and Management, 6(3), 208-215.

  • Altman, E. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 24(3), 589-609.

  • Altman, E. I., & Hotchkiss, E. (2006). Corporate financial distress and bankruptcy. Wiley and Sons: New Jersey.

  • Altman, E. I., Drozdowska, M. I., Erkki, K. L., & Suvas, A. (2017). Financial distress prediction in an international context: A review and empirical analysis of Altman’s Z-score model. Journal of International Financial Management & Accounting, 28(2), 131-170.

  • Andrade, G., & Kaplan, S. (1998). How costly is financial (not economic) financial distress - Evidence from highly leveraged transactions that became distressed. Journal of Finance, 53(2), 1443-1493.

  • Asgharian, H. (2003). Are highly leveraged firms more sensitive to an economic downturn?. The European Journal of Finance, 9(2), 219-241.

  • Beaver, W. (1966). Financial ratios as predictors of bankruptcy. Journal of Accounting Research, 6(1), 71-102.

  • Beaver, W. (1968). The information content of annual earnings announcements. Journal of Accounting Research, 6(1), 67-92.

  • Bergstrom, C., & Sundgren, S. (2002). Restructuring activities and changes in performance following financial distress. SNS Occasional Paper No. 88.

  • Bolton, P., & Scharfstein, D. S. (1990). A theory of predation based on agency problems in financial contracting. American Economic Review, 80(3), 93-106.

  • Casey, C., & Bartczak, N. (1984). Cash flow: It’s not the bottom line. Harvard Business Review, 4(2), 60-66.

  • Hillegeist, S., Keating, E., & Lundstedt, K. (2004). Assessing the probability of bankruptcy. Review of Accounting Studies, 9(3), 5-34.

  • Jandik, T., & Makhija, A. K. (2005). Debt, debt structure and corporate performance after unsuccessful takeovers: Evidence from targets that remain independent. Journal of Corporate Finance, 11(2), 882-914.

  • Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and own ership structure. Journal of Financial Economics, 11(2), 5-50.

  • Lischuts, S., & Jacobi, A. (2010). Predicting bankruptcy: Evidence from Israel. International Journal of Business and Management, 5(4), 33-141.

  • Mamo, A. Q. (2011). Applicability of Altman model in predicting financial distress of commercial banks in Kenya. University of Nairobi. Retrieved from http://erepository.uonbi.ac.ke/bitstream/handle/11295/12760/Mamo_Applicability%20of%20Altman%20(1968)%20model%20in%20predicting%20financial%20distress%20of%20commercial%20banks%20in%20Kenya.pdf?sequence=4.14

  • Merton, R. (1974). On the pricing of corporate debt: The risk structure of interest rates. The Journal of Finance, 29(2), 449-470.

  • Modigliani, F., & Merton, H. M. (1963). Corporate income taxes and the cost of capital: A correction. The American Economic Review, 53(3), 433-443.

  • Mohammed, S. (2016). Bankruptcy prediction by using the Altman Z-score model in Oman: A case study of Raysut cement company SAOG and its subsidiaries. Australasian Accounting, Business and Finance Journal, 10(4), 70-80.

  • Novaes, W., & Zingales, L. (1993). Financial distress as a collapse of incentive schemes. Unpublished manuscript, University of Chicago. Retrieved from https://www.researchgate.net/publication/228264048_Financial_Distress_as_a_Collapse_of_Incentives. Accessed on August, 2018.

  • NurAdiana, H. A., Halim A., & Ahmad, H. R. (2008). Predicting corporate failure of Malaysia’s listed companies: Comparing multiple discriminant analysis, logistic, and hazard model. International Journal of Finance and Economics, 15(3), 201-217.

  • Ohlson, J. (1980). Financial ratios and probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109-131.

  • Opler, T. C., & Titman, S. (1994). Financial distress and corporate performance. The Journal of Finance, 49(3), 1015-1040.

  • Outecheva, N. (2007). Corporate financial distress: An empirical analysis of distress risk (Doctoral dissertation,. University of St. Gallen Graduate School of Business Administration, Economics, Law and Social Sciences, Russia). Retrieved from http://www1.unisg.ch/www/edis.nsf/SysLkpByIdentifier/3430/$FILE/dis3430.probaility of default

  • Pandey, I. M. (2005). Management accounting. New Delhi: Vikas Publishing.

  • Sajjan, R. (2016). Predicting bankruptcy of selected firms by applying Altman’s Z-score model. International Journal of Research Granthaalayah, 4(4), 152-158.

  • Shumway, T. (2001). Forecasting bankruptcy more accurately: A simple hazard model. Journal of Business, 74(1), 101-124.

  • Pradhan, R. (2014). Z score estimation for Indian banking sector. International Journal of Trade, Economics, and Finance, 5(6), 516-520.

  • Reisz, A. S., & Perlich, C. (2007). A market-based framework for bankruptcy prediction. Journal of Financial Stability, 3(2), 85-131.

  • Sanesh, C. (2016). The analytical study of Altman Z score on Nifty 50 companies. International Journal of Management and Social Sciences, 3(3), 433-438.

  • Sulub, S. A. (2014). Testing the predictive power of Altman’s revised Z’ model: The case of 10 multinational companies. Research Journal of Finance and Accounting, 21(5), 174-185.

  • Taffler, R. J. (1984). Empirical models for the monitoring of UK corporations. Journal of Banking and Finance, 8(2), 199-227.

  • Tan, T. K. (2012). Financial distress and firm performance: Evidence from the Asian financial crisis. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.475.81&rep=rep1&type =pdf. Accessed on Oct 1, 2016.

  • Vayanos, D. (2004). Flight to quality, flight to liquidity, and the pricing of risk. Working Paper 10327, NBER Working Paper Series. Retrieved from https://www.nber.org/papers/w10327.pdf. Accessed on Oct 10, 2014.

  • Williams, J. R., Haka, S. F., & Bettner, M. S. (2006). Financial and Managerial Accounting. New Delhi: Tata McGraw Hill.

  • Wruck, K. (1990). Financial distress, reorganization, and organizational efficiency. Journal of Financial Economics, 27(2), 419-444.

  • Wu, Y., Gaunt, C., & Gray, S. (2010). A comparison of alternative bankruptcy prediction models. Journal of Contemporary Accounting & Economics, 6(1), 34-45.

  • Zmijewski, M. E. (1984). Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research, 22(2), 59-82.


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  • Financial Distress and Bank Performance:A Study of Select Indian Banks

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Authors

Japneet Kaur
MCM DAV College, Chandigarh, India

Abstract


Financial distress is technically used to evaluate the financial status of the firms in terms of insolvency and bankruptcy. In view of the rising corporate scams such as Enron, Parmalat, Satyam, Punjab and Sind bank, etc., it is imperative to predict financial distress as the fallout of bankruptcy causes heavy losses to the companies and thus affects the national economy. In particular, the banking sector plays a vital role in the economic development of a country. The main purpose of this study is to assess the financial performance of the banking sector in India using Altman (1968) Z-score model for the period 2012-2017. Z-score has been used as a tool to evaluate the credibility of the banks by estimating the Z-score values of the select banks in India. This value is useful when these banks demand loans from the RBI or any other funding agency. Thereafter, the effect of financial distress on the performance of banks has also been assessed by taking Tobin’s Q as the performance measure. The results revealed that distressed stocks outperform non-distressed stocks during the market upturns.

Keywords


Financial Distress, Banking Sector, Tobin’s Q.

References