Predicting Going Concern of Companies Using the Tone of Auditor Reporting

[1] Altman, E.I. , 1968, Financial ratios, discriminant analysis, and the prediction of corporate bankruptcy, Journal of Finance, 23 , 589-609.
[2] Altman, E.I., Sabato, G., & Wilson, N., 2010, The value of non- nancial information in small and medium-sized enterprise risk management, Journal of Credit Risk, 2 , 95-127.
[3] Banimahd, B., Arabi, M. & Hasanpor, Sh., 2016, Experimental research and methodology in accounting, Termeh Publications.
[4] Campbell, J. Y., Hilscher, J., & Szilagyi, J. , 2008, In search of distress risk, The Journal of Finance, 63 , 2899-2939.

[5] Davis, A. K., Ge, W., Matsumoto, D., & Zhang, J. L., 2015, The effect of managerspeci c optimism on the tone of earnings conference calls, Review of Accounting Studies,20(2), 639673.
[6] Drass, K. A. , 2019, Text Analysis and Text-Analysis Software: A Comparison of Assumptions, New Technology in Sociology, , 155162.
[7] Elsayed, M., Elsayed, M., Elshandidy, T., & Elshandidy, T. , 2020, Do narrative-related disclosures predict corporate failure? Evidence from UK non- nancial publicly quoted  rms, International Review of Financial Analysis, 71, 101555.
[8] Feldman, R., Govindaraj, S., Livnat, J., & Segal, B. , 2010, Management's tone change, post earnings announcement drift and accruals, Review of Accounting Studies, 15(4), 915953.
[9] Garcia, D., 2013, Sentiment during recessions, The Journal of Finance, 68(3), 12671300.
[10] Grunert, J.P., Norden, L., Weber, M., & Weber, M., 2005, The role of non- nancial factors in internal credit ratings, Journal of Banking and Finance, 29, 509-531.
[11] Hamer, M.M. , 1983, Failure prediction: sensitivity of classi cation accuracy to alternative statistical methods and variable sets, Journal of Accounting and Public policy, 2, 289-307.
[12] Henry, E. , 2008, Are investors in uenced by how earnings press releases are written?, The Journal of Business Communication(1973), 45(4), 363-407.
[13] Hobbs, J. R., Walker, D. E., & Amsler, R. A. , 1982, Natural language access to structured text, Proceedings of the ninth Conference on Computational Linguistics.
[14] Hotho, A., Nurnberger, A., & Paass, G. , 2005, A brief survey of text mining, LDV Forum, 20, 19-62.
[15] Huang, X., Teoh, S. H., & Zhang, Y. , 2013, Tone management, The Accounting Review,89(3), 10831113.
[16] Jo, N., & Shin, K. , 2016, Bankruptcy prediction modeling using qualitative information based on big data analytics.
[17] Kashanipoor, M., Aghaee, M.A., & Mohseni Namaghi, D. , 2020, Information Disclosure Tone and Future Performance, Accounting and Auditing Review, 26(4), 570-594. (In Persian)
[18] Kou, J. , 2022, Analysing Housing Price in Australia with Data Science Methods, Doctoral dissertation, Victoria University.
[19] Kumar, L., & Bhatia, P. , 2013, Text mining: concepts, process, and applications, Journal of Global Research in Computer Sciences, 4, 36-39.
[20] Law, K. K., & Mills, L. F. , 2015, Taxes and  nancial constraints: Evidence from linguisticcues, Journal of Accounting Research, 53(4), 777819.
[21] Li, Y., & Wang, Y. , 2018, Machine learning methods of bankruptcy prediction using accounting ratios, Open Journal of Business and Management, 6, 1-20.
[22] Leshno, M., & Spector, Y. , 1996, Neural network prediction analysis: the bankruptcy case, Neurocomputing, 10, 125-147.
[23] Levin, A., Lin, C.F., & Chu, C-S.J. , 2002, Unit root test in panel data, Journal of Econometrics, 108, 1-22.
[24] Lohmann, C., & Ohliger, T. , 2020, Bankruptcy prediction and the discriminatory power of annual reports: empirical evidence from  nancially distressed German companies, Journal of Business Economics, 90(1), 137-172.
[25] Lopatta, K., Gloger, M. A., & Jaeschke, R. , 2017, Can language predict bankruptcy? The explanatory power of tone in 10K  lings, Accounting Perspectives, 16(4), 315-343.
[26] Loughran, T., & McDonald, B. , 2011, When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks, The Journal of Finance, 66(1), 3565.
[27] Marti Hearst, What is Text Mining?, https://people.ischool.berkeley.edu/ hearst/text- mining.html.
[28] Mayew, W.J., Sethuraman, M., & Venkatachalam, M. , 2015, MD&A Disclosure and the Firm's Ability to Continue as a Going Concern, The Accounting Review, 90(4), 1621-1651.
[29] Merkl-Davies, D. M., Brennan, N. M., 2007, Discretionary Disclosure Strategies in Corporate Narratives: Incremental Information or Impressions Management?, Journal of Accounting Literature, 27, 116- 196.
[30] Mirali, M., Gholami moghaddam, F., Hesarzadeh, R. , 2018, Investigation of the Relationship between Financial Reporting Tone with Future Corporate Performance and Market Return, Financial Accounting Knowledge, 5(3), 81-98. (In Persian)

[31] Najafzadeh, A., Farzinvash, A., Yosefi Sheikhrobat, M. & Naser, A. , 2021, Asymmetric behavior of the effectiveness of  scal policies in the smooth transition process, Doctoral dissertation,Tehran, Mo d University.
[32] NieSSner, T., Gross, D. H., & Schumann, M. , 2022, Evidential Strategies in Financial Statement Analysis: A Corpus Linguistic Text Mining Approach to Bankruptcy Prediction, Journal of Risk and Financial Management, 15(10), 459.
[33] Odom, M.D., & Sharda, R. , 1990, A neural network model for bankruptcy prediction, Joint international conference on neural networks, 2, 163-168.
[34] Ohlson, J.A. , 1980, Financial ratios and the probabilistic prediction of bankruptcy, Journal of accounting research, 18, 109-131.
[35] Pervan, I., & Kuvek, T. , 2013, The relative importance of  nancial ratios and non nancial variables in predicting insolvency, Croatian Operational Research Review, 4, 187-197.
[36] Rowland, Z., Kasych, A., & Suler, P., 2021, Prediction of  nancial distress: case of mining enterprises in Czech Republic, Ekonomicko-manazerske spektrum, 15(1), 1-14.
[37] Shaw, M.J., & Gentry, J.A. , 1990, Inductive learning for risk classi cation, IEEE expert, 5, 47-53.
[38] Shin, K., Lee, T.S., & Kim, H., 2005, An application of support vector machines in the bankruptcy prediction model, Expert syst. Appl., 28, 127-135.
[39] Siano, F., & Wysocki, P., 2021, Transfer learning and textual analysis of accounting disclosures: Applying big data methods to small (er) datasets, Accounting Horizons, 35(3),217-244.
[40] Visvanathan, G. , 2021, Is information in deferred tax valuation allowance useful in pre- dicting the  rms ability to continue as a going concern incremental to MD&A disclosures and auditors going concern opinions?, International Journal of Disclosure and Governance,18(3), 223-239.
[41] Yekini, L. S., Wisniewski, T. P., & Millo, Y. , 2016, Market reaction to the positiveness of annual report narratives, The British Accounting Review, 48(4), 415430.
[42] Zhang, Z., Luo, M., Hu, Z., & Niu, H. , 2022, Textual Emotional Tone and Financial Crisis Identi cation in Chinese Companies: A Multi-Source Data Analysis Based on Machine Learning, Applied Sciences, 12(13).
[43] Zhao, Y., Wei, S., Guo, Y., Yang, Q., & Kou, G. , 2022, FisrEbp: Enterprise Bankruptcy Prediction via Fusing its Intra-risk and Spillover-Risk.