Financial Distress Prediction through the Combination of Cash Flow Components of Listed Companies in the Stock Exchange of Thailand
Keywords:
cash flows from operating activities, cash flows from investing activities, cash flows from financing activities, combinations of cash flow components, financial distressAbstract
The purpose of this study is to investigate the ability of the cash flows data in predicting financial distress of the companies listed in the Stock Exchange of Thailand. Financial distress is represented by three consecutive years of corporate net losses and cash flow data (which is the combination of cash flows from three activities: operating (CFO), investing (CFI), and financing (CFF)). Based on Jantadej (2006), there are eight combinations(CFO,CFI,CFF), including(-,+,+), (-,+,-), (-,-,+), (+,+,-), (+,-,+), (+,-,-), (+,+,+), and (-,-,-). Data from 590 Thai listed companies were collected during the period from 2007 to 2016; and logistic regression analyses are employed. The result shows that cash flow data in the year before the occurrence of financial distress has high predictability, and it suggests that if a company has negative CFO and positive CFI in the current year then it tends to have financial distress in the upcoming year. Furthermore, the result reveals that debt ratio, ROA, and retained earrings to total assets have a significantly negative relationship with the financial distress.
References
Allison, P.D. (1999). Logistic Regression Using the SAS® System: Theory and Application.Cary, NC: SAS Institute.
Altman, E.I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x
Aramtiantamrong, N. (2011). Bankruptcy prediction: Evidence in Thailand. Master independent study, Master of Sciences (Financial Management), Thammasat University, Bangkok.
Banks, E. (2005). Financial Lexicon, A Compendium of Financial Definitions, Acronyms, and Colloquialisms. 1st edition: Palgrave Macmillan Publishing.
Beaver, W.H. (1966). Financial Ratios as Predictors of Failure. Journal of Accounting Research, 4(3), 71-111. https://doi.org/10.2307/2490171
Beaver, W.H. (1968). Alternative accounting measures as predictors of failure. Accounting Review, 43(1), 113-122.
Casey, C. &Bartczak, N. (1985). Using operating cash flow data to predict financial distress: some extensions. Journal of Accounting Research, 23(1), 384-401. https://doi.org/10.2307/2490926
Chaghadari, M.F. (2011). Corporate governance and firm performance. International Conference on Sociality and Economics Development, 10, 484-489.
Cheniam, S. (2001). Prediction model of potential delisted companies in the stock exchange of Thailand. Chulalongkorn Business Review, 13(51), 34-44.
Cholpaisal, P. (2014). Business warning: Case study companies listed on the stock exchange of Thailand. Suthiparithat Journal, 30(94), 238-249.
Deakin, E. (1972). A discriminant analysis of predictors of business failure. Journal of Accounting Research, 10(2), 167-179. https://doi.org/10.2307/2490225
DeAngelo, H. &DeAngelo, L. (1990). Dividend policy and financial distress: an empirical investigation of troubled NYSE firms. The Journal of Finance, 45(5), 1415-1431. https://doi.org/10.1111/j.1540-6261.1990.tb03721.x
Fallahpour, S. (2004). Prediction of bankruptcy by usage of neural network model. Master dissertation. Faculty of Management, University of Tehran. Tehran.
Federation of Accounting Professions. (2015). TAS 7: Statement of cash flows (Bound volume 2015). Bangkok: n.p.
Gentry, J.A., Newbold, P., & Withford, D.T. (1990). Profiles of cash flow components. Financial Analysts Journal, 46(4), 41-48. https://doi.org/10.2469/faj.v46.n4.41
Gholamreza, K., Vahid, B. &Mehrdad, B. (2011). Ability of combinations of cash flow components to predict financial distress. TeorijairprakTika, 12(3), 277-285. https://doi.org/10.3846/btp.2011.28
Gilbert, L.R., Menon, K. & Schwartz, K.B. (1990). Predicting bankruptcy for firms and financial distress. Journal of Business Finance and Accounting, 17(1), 161-171. https://doi.org/10.1111/j.1468-5957.1990.tb00555.x
Gomez, L. (2002). Enron-a case for better understanding of cash flows. Business Credit. 104(July/August), 12-13.
Hosmer, D.W. &Lemeshow, S. (2000). Applied Logistic Regression. New York, NY: John Wiley & Sons. https://doi.org/10.1002/0471722146
independent study, Master of Economics (Business Economics), Faculty of Economics, Thammasat University, Bangkok.
Jantadej, P. (2006). Using the Combination of Cash Flow Component to Predict Financial Distress. Doctoral dissertation. Graduate College. University of Nebraska
Khermkhan, J. & Chancharat, S. (2013). Financial distress prediction methods. Executive Journal, 33(4), 34-41.
Khemnguad, E. (2011). Development of Altman's EM-Score model for predicting financial distress of listed companies in the stock exchange of Thailand. Master independent study, M.B.A., Bangkok University, Bangkok.
Largay, J. A. & Stickney, C.P. (1980). Cash flows, ratio analysis and the company bankruptcy. Financial Analysts Journal, 36(4), 51-54. https://doi.org/10.2469/faj.v36.n4.51
Nammeung, A. (2007). Factors as indicators of financial failure: A case of listed companies on the stock exchange of Thailand. Master thesis, Master of Accountancy, Kasetsart University, Bangkok.
Ohlson, J.A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109-131. https://doi.org/10.2307/2490395
Pastena, V. & Ruland, W. (1986). The merger/bankruptcy alternative. The Accounting Review, 61(2), 288-301.
Phumwiset, W. (2011). Using financial ratio in predicting financial distress of listed companies in the stock exchange of Thailand. Master thesis, Master of Accountancy, Kasetsart University, Bangkok.
Pilasri, P. & Phadoongsitthi, M. (2011). Bankruptcy prediction model using discriminant analysis. Journal of Accounting Profession, 7(18), 26-42.
Pongsatat, S., Ramage, J., & Lawrence, H. (2004). Bankruptcy prediction for large and small firms in Asia: A comparison of Ohlson and Altman. Journal of Accounting and Governance, 1(2), 1-13.
Sanmuangkaew, W. (2013). Bankruptcy prediction among listed companies using accounting and market variables evidence from Thailand. Master independent study, Master of Sciences (Financial Management), Thammasat University, Bangkok.
Sayari, N. & Can SimgaMugan F.N. (2013). Cash flow statement as an evidence for financial distress. Universal Journal of Accounting and Finance, 1(3), 95 - 102. https://doi.org/10.13189/ujaf.2013.010302
Schellenger, M. & Cross, J.N. (1994). FASB 95, Cash flow and bankruptcy. Journal of Economics and Finance, 18(3), 261-274. https://doi.org/10.1007/BF02920486
Siriwattanatrakul, C. (2002). A case study of listed companies in hotel, entertainment and hospital sector. Master independent study, M.B.A., Kasetsart University, Bangkok.
Tanasuteeerachai, C. (2012). Predicting financial distress. Master independent study, Master of Sciences (Financial Management), Thammasat University, Bangkok.
Thani, P. & Asavarangpipop, P. (2003). Failure prediction model on performance of agricultural cooperatives' rice mills in northern Thailand. Journal of Agriculture, 19(2), 167-175. https://doi.org/10.1108/00215070380001148
Tharuea-Rak, K. (2005). Bankruptcy prediction model using Logit Model: Case study of listed companies on the stock exchange of Thailand during 2002-2004.
Thitisutthi, N. (2556). Bankruptcy prediction model using Logit Model. Master independent study, Master of Accountancy, Thammasat University, Bangkok.
Thumacheewan, L. (2006). Using financial information in predicting financial distress of REHABCO in the stock exchange of Thailand. Master independent study, M.B.A., Kasetsart University, Bangkok.
Tirapat, S. & Nittayasetwat, A. (1999). An investigation of thai listed firms' financial distress using macro and micro variables. Multinational Finance Journal, 3(2), 103-125. https://doi.org/10.17578/3-2-2
Vanichbuncha, K. (2001). Multivariate Analysis by SPSS for Windows. 2ed edition. Bangkok: Chulalongkorn University Printing House.
Ward, T.J. & Foster, B.P. (1997). A note on selecting a response measure for financial distress. Journal of Business Finance and Accounting, 24(6), 869-879. https://doi.org/10.1111/1468-5957.00138
Ward, T.J. (1992). The incremental predictive ability of net and gross cash flows using four-state ordinal models of financial distress.The Southern Business and Economic Journal, October, 26-44.
Ward, T.J. (1994). Cash Flow information and the prediction of financially distressed mining, oil and gas firms: A comparative study. Journal of Applied Business Research, 10(3), 78-87. https://doi.org/10.19030/jabr.v10i3.5927
Wattanawong, P. (2000). The model for predicting companies vulnerable to be delisted from the stock exchange of Thailand. Master thesis, Master of Accountancy, Kasetsart University, Bangkok.
Wichaiyut, K. (2003). Using financial information in predicting rehabilitated property development business listed in the stock exchange of Thailand. Master thesis, Master of Sciences (Financial), Chulalongkorn University, Bangkok.
Zmijewski, M.E. (1984). Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research, 22, 59-82. https://doi.org/10.2307/2490859
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2020 https://creativecommons.org/licenses/by-nc-nd/4.0/
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
