Öz
The
financial situation of enterprises is subject to both the practitioners and the
researchers. Especially in the last twenty years, it has been revealed that
external dynamics as well as internal dynamics are influential in the
operations of the enterprises with the removal of barriers to capital and the
globalisation of the capital markets. Many enterprises face financial failure
due to these internal and external causes. The fragility of emerging markets,
especially during times of crisis, increases the risk of failure. In the event
of financial failure, companies may face various negative situations. The delay
of firms in taking measures against these types of negativities increases the
probability of bankruptcy. For this reason, it is very important to be able to
predict the financial failures of firms. Several models have been developed in
the literature to predict financial failure. Some of these models are based on
accounting data and others are based on market data. Artificial neural networks
play a significant role in financial failure prediction models. With this
study, it is aimed to guide the researchers about the use of artificial neural
networks as a financial failure prediction model.
Anahtar Kelimeler
Financial Failure Financial Distress Reasons of Financial Failure Financial Failure Prediction Models Artificial Neural Networks
Kaynakça
- Ahn B.S.; Cho S.S.; Kim C.Y. (2000). “The Integrated Methodology of Rough Set Theory and Artificial Neural Network for Business Failure Prediction”, Expert Systems Applications, 18, p.65–74. Akgüç, Ö. (2013). “Finansal Yönetim”, 8.Baskı, İstanbul: Avcıol Basın Yayın. Akkaya,G. C.; Demirli E.; Yakut, H.Ü. (2009). “İşletmelerde Finansal Başarısızlık Tahminlemesi: Yapay Sinir Ağları Modeli ile İMKB Üzerine Bir Uygulama”, Eskişehir Osman Gazi Üniversitesi Sosyal Bilimler Dergisi, (10) 2 s.187-216. Altman, E. (1968). “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy”, The Journal of Finance, 23(4), p.589-609. Aydın, N.; Başar, M.; Coşkun, M. (2010). “Finansal Yönetim”, 2.Baskı, Ankara: Detay Yayıncılık. Barniv, R.; Agarwal, A.; Leach, R. (1997). “Predicting the Outcome Following Bankruptcy Filing: A Three-state Classification Using Neural Networks”, Intelligent Systems in Accounting, Finance and Management, 6 (3), p.177–194. Beaver, W. (1966). “Financial Ratios As Predictors of Failure”, Journal of Accounting Research, 4, p.71-111. Beaver, W. (1968). “Market Prices, Financial Ratios, and the Prediction of Failure”, Journal of Accounting Research, 6 (2), p.179-192. Brigham, E.F.; Houston, J.F. (2012). “Fundamentals of Financial Management”, Mason: South-Western Cengage Learning. Caballero, R.J.; Hammour, M.L. (1991). “The Cleansing Effect of Recessions”, NBER Working Paper No. 3922. Casey, C.; Bartczak, N. (1985). “Using Operating Cash Flow Data To Predict Financial Distress - Some Extensions”, Journal of Accounting Research, 23 (1), p.384-401. Chen, W.S.; Du, Y. (2009). “Using Neural Networks and Data Mining Techniques for the Financial Distress Prediction Model”, Expert Systems with Applications, 36 (2), p.4075-4086. Clarence N.W.; Tan, H.D. (2001). "A Study of Using Artificial Neural Networks to Develop An Early Warning Predictor for Credit Union Financial Distress with Comparison to the Probit Model", Managerial Finance, 27 (4), p.56-77. Coats, P.; L. Fant, (1993). “Recognizing Financial Distress Patterns Using a Neural Network Tool”, Financial Management, 22 (3), p.142-155. Dambolena, I.; Khoury, S. (1980). “Ratio Stability and Corporate Failure”, The Journal of Finance, 35(4), p.1017-1026. Deakin, E. (1972). “A Discriminant Analysis of Predictors of Business Failure”, Journal of Accounting Research, 10 (1), p.167-179. Edmister, R. (1972). “An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction”, The Journal of Financial and Quantitative Analysis, 7(2), p.1477-1493. Etheridge, H.L.; Sriram, L.M. (1997). “A Comparison of the Relative Costs of Financial Distress Models: Artificial Neural Networks, Logit and Multivariate Discriminant Analysis”. Intelligent Systems in Accounting, Finance and Management, 6 (3), p.235–248. Ercan, İ. (2008). “Tasfiye, Tasfiye Dönemi ve Tasfiye Kararının Tespiti”, Mali Çözüm Dergisi, Sayı:85, 2008, s.189-201. Erdönmez, P.A. (2006). “Aktif Menkul Kıymetleştirmesi”, Bankacılar Dergisi, 56, s.75-84. Hopenhayn, H. (1992). “Entry, Exit, and firm Dynamics in Long Run Equilibrium”, Econometrica, 60 (5), p.1127-1150. Koh, H.C.; Low, C.K. (2004). “Going Concern Prediction Using Data Mining Techniques”, Managerial Auditing Journal, 19 (3), p.462-476. Lee, T.-S.; Chen I.-F. (2005). “A Two-Stage Hybrid Credit Scoring Model Using Artificial Neural Networks and Multivariate Adaptive Regression Splines”, Expert Systems with Applications, 28, p.743-752. Lin, T-H. (2009). “A Cross Model Study of Corporate Financial Distress Prediction in Taiwan: Multiple Discriminant Analysis, Logit, Probit and Neural Networks Models”. Neurocomputing, 72, p.3507-3516. Mbat, D.O.; Eyo, I.E. (2013). “Corporate Failure: Causes and Remedies”, Business and Management Research, 2 (4), p.19-24. Merwin, C.L. (1943). “Financing Small Corporations in Five Manufacturing Industries”, The American Econometric Review, 33 (2), p.430-432. Mossman, C.E.; Bell, G.G.; Swartz, L.M.; Turtle, H. (1998). “An Empirical Comparison of Bankruptcy Models”, Financial Review, 33 (2), p.1–226. Ohlson, J. (1980). “Financial Ratios and the Probabilistic Prediction of Bankruptcy”, Journal of Accounting Research, 18 (1), p.109-131. O’Leary, D.E. (1998). “Using Neural Networks to Predict Corporate Failure”, International Journal of Intelligent Systems in Accounting, Finance & Management, 7, p.187-197. Patrick, P.J.F. (1932). “A Comparison of Ratios of Successful Industrial Enterprises With Those of Failed Firms”, Certified Public Accountant. p.656-662. Sinkey, J.F.; Walker, D.A. (1975). “Problem Banks: Identification and Characteristics”, Federal Deposit Insurance Corporation, 74 (3), p.8-24. Weston, J.F.; Brigham, E. (1981). “Managerial Finance”, Dryden Pres, 7. Baskı. Vuran, B. (2012). “Şirketlerin Finansal Açıdan Sorunlu Olmasına İlişkin Model Çalışması: Türkiye Üzerine Bir Araştırma”, İstanbul: Türkmen Kitabevi. 6102 sayılı Türk Ticaret Kanunu. 2004 sayılı İcra İflas Kanunu.
Öz
İşletmelerin finansal durumları gerek uygulamacılar gerekse araştırmacılar
tarafından incelemelere konu olmaktadır. Özellikle son yirmi yılda sermayenin
önündeki engellerin kalkması ve sermaye piyasalarının küresel bir hal alması
işletmelerin faaliyetlerini sürdürmelerinde içsel dinamikler kadar dışsal
dinamiklere de önem vermeleri gerektiğini ortaya koymuştur. Birçok işletme bu
içsel ve dışsal nedenlerden dolayı finansal başarısızlık ile karşı karşıya
kalmaktadır. Özellikle kriz dönemlerinde gelişmekte olan piyasaların
kırılganlığı işletmelerin başarısızlık riskini arttırmaktadır. Finansal
başarısızlık karşısında firmalar çeşitli olumsuz durumlarla yüz yüze kalabilmektedir.
Firmaların bu tip olumsuzluklara karşı önlem almakta gecikmesi iflas
olasılıklarını arttırmaktadır. Bu sebeple firmaların finansal
başarısızlıklarının tahmin edilebilmesi oldukça önemlidir. Finansal
başarısızlığın tahmin edilebilmesi için literatürde birçok model
geliştirilmiştir. Bu modellerden bazıları muhasebe verilerine, bazıları da
piyasa verilerine dayalıdır. Finansal başarısızlık tahmin modelleri içerisinde
yapay sinir ağları önemli bir yer tutmaktadır. Bu çalışma ile finansal
başarısızlık tahmin modeli olarak yapay sinir ağlarının kullanımı ile ilgili
olarak araştırmacılara yol gösterilmesi amaçlanmaktadır.
Anahtar Kelimeler
Finansal Başarısızlık Finansal Sıkıntı Finansal Başarısızlık Nedenleri Finansal Başarısızlık Tahmin Modelleri Yapay Sinir Ağları
Kaynakça
- Ahn B.S.; Cho S.S.; Kim C.Y. (2000). “The Integrated Methodology of Rough Set Theory and Artificial Neural Network for Business Failure Prediction”, Expert Systems Applications, 18, p.65–74. Akgüç, Ö. (2013). “Finansal Yönetim”, 8.Baskı, İstanbul: Avcıol Basın Yayın. Akkaya,G. C.; Demirli E.; Yakut, H.Ü. (2009). “İşletmelerde Finansal Başarısızlık Tahminlemesi: Yapay Sinir Ağları Modeli ile İMKB Üzerine Bir Uygulama”, Eskişehir Osman Gazi Üniversitesi Sosyal Bilimler Dergisi, (10) 2 s.187-216. Altman, E. (1968). “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy”, The Journal of Finance, 23(4), p.589-609. Aydın, N.; Başar, M.; Coşkun, M. (2010). “Finansal Yönetim”, 2.Baskı, Ankara: Detay Yayıncılık. Barniv, R.; Agarwal, A.; Leach, R. (1997). “Predicting the Outcome Following Bankruptcy Filing: A Three-state Classification Using Neural Networks”, Intelligent Systems in Accounting, Finance and Management, 6 (3), p.177–194. Beaver, W. (1966). “Financial Ratios As Predictors of Failure”, Journal of Accounting Research, 4, p.71-111. Beaver, W. (1968). “Market Prices, Financial Ratios, and the Prediction of Failure”, Journal of Accounting Research, 6 (2), p.179-192. Brigham, E.F.; Houston, J.F. (2012). “Fundamentals of Financial Management”, Mason: South-Western Cengage Learning. Caballero, R.J.; Hammour, M.L. (1991). “The Cleansing Effect of Recessions”, NBER Working Paper No. 3922. Casey, C.; Bartczak, N. (1985). “Using Operating Cash Flow Data To Predict Financial Distress - Some Extensions”, Journal of Accounting Research, 23 (1), p.384-401. Chen, W.S.; Du, Y. (2009). “Using Neural Networks and Data Mining Techniques for the Financial Distress Prediction Model”, Expert Systems with Applications, 36 (2), p.4075-4086. Clarence N.W.; Tan, H.D. (2001). "A Study of Using Artificial Neural Networks to Develop An Early Warning Predictor for Credit Union Financial Distress with Comparison to the Probit Model", Managerial Finance, 27 (4), p.56-77. Coats, P.; L. Fant, (1993). “Recognizing Financial Distress Patterns Using a Neural Network Tool”, Financial Management, 22 (3), p.142-155. Dambolena, I.; Khoury, S. (1980). “Ratio Stability and Corporate Failure”, The Journal of Finance, 35(4), p.1017-1026. Deakin, E. (1972). “A Discriminant Analysis of Predictors of Business Failure”, Journal of Accounting Research, 10 (1), p.167-179. Edmister, R. (1972). “An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction”, The Journal of Financial and Quantitative Analysis, 7(2), p.1477-1493. Etheridge, H.L.; Sriram, L.M. (1997). “A Comparison of the Relative Costs of Financial Distress Models: Artificial Neural Networks, Logit and Multivariate Discriminant Analysis”. Intelligent Systems in Accounting, Finance and Management, 6 (3), p.235–248. Ercan, İ. (2008). “Tasfiye, Tasfiye Dönemi ve Tasfiye Kararının Tespiti”, Mali Çözüm Dergisi, Sayı:85, 2008, s.189-201. Erdönmez, P.A. (2006). “Aktif Menkul Kıymetleştirmesi”, Bankacılar Dergisi, 56, s.75-84. Hopenhayn, H. (1992). “Entry, Exit, and firm Dynamics in Long Run Equilibrium”, Econometrica, 60 (5), p.1127-1150. Koh, H.C.; Low, C.K. (2004). “Going Concern Prediction Using Data Mining Techniques”, Managerial Auditing Journal, 19 (3), p.462-476. Lee, T.-S.; Chen I.-F. (2005). “A Two-Stage Hybrid Credit Scoring Model Using Artificial Neural Networks and Multivariate Adaptive Regression Splines”, Expert Systems with Applications, 28, p.743-752. Lin, T-H. (2009). “A Cross Model Study of Corporate Financial Distress Prediction in Taiwan: Multiple Discriminant Analysis, Logit, Probit and Neural Networks Models”. Neurocomputing, 72, p.3507-3516. Mbat, D.O.; Eyo, I.E. (2013). “Corporate Failure: Causes and Remedies”, Business and Management Research, 2 (4), p.19-24. Merwin, C.L. (1943). “Financing Small Corporations in Five Manufacturing Industries”, The American Econometric Review, 33 (2), p.430-432. Mossman, C.E.; Bell, G.G.; Swartz, L.M.; Turtle, H. (1998). “An Empirical Comparison of Bankruptcy Models”, Financial Review, 33 (2), p.1–226. Ohlson, J. (1980). “Financial Ratios and the Probabilistic Prediction of Bankruptcy”, Journal of Accounting Research, 18 (1), p.109-131. O’Leary, D.E. (1998). “Using Neural Networks to Predict Corporate Failure”, International Journal of Intelligent Systems in Accounting, Finance & Management, 7, p.187-197. Patrick, P.J.F. (1932). “A Comparison of Ratios of Successful Industrial Enterprises With Those of Failed Firms”, Certified Public Accountant. p.656-662. Sinkey, J.F.; Walker, D.A. (1975). “Problem Banks: Identification and Characteristics”, Federal Deposit Insurance Corporation, 74 (3), p.8-24. Weston, J.F.; Brigham, E. (1981). “Managerial Finance”, Dryden Pres, 7. Baskı. Vuran, B. (2012). “Şirketlerin Finansal Açıdan Sorunlu Olmasına İlişkin Model Çalışması: Türkiye Üzerine Bir Araştırma”, İstanbul: Türkmen Kitabevi. 6102 sayılı Türk Ticaret Kanunu. 2004 sayılı İcra İflas Kanunu.
Ayrıntılar
| Konular | İşletme |
|---|---|
| Bölüm | Araştırma Makaleleri |
| Yazarlar | |
| Yayımlanma Tarihi | 28 Aralık 2017 |
| Gönderilme Tarihi | 10 Aralık 2017 |
| Kabul Tarihi | 26 Aralık 2017 |
| Yayımlandığı Sayı | Yıl 2017 Cilt: 2 Sayı: 4 |
