چکیده:
هدف: پژوهش حاضر با هدف بررسی قدرت مدلهای پیشبینی درماندگی مالی، ضمن ارائه یک مدل ترکیبی، به بررسی مدل استخراج شده با مدلهای آلتمن و مدل مرتون در پیشبینی درماندگی در سه گروه شرکتهای سالم، در حال درماندگی و درمانده میپردازد.
روش: در پژوهش حاضر، پس از بررسی مطالعات گذشته، 47 متغیر تأثیرگذار روی درماندگی مالی، شامل متغیرهای حسابداری، بازاری و شاخصهای کلان اقتصادی شناسایی شد و با تأکید بر فراوانی و عملکرد موفق این نسبتها در مطالعات گذشته و انجام آزمونهای آماری، شاخصهای نهایی انتخاب شدند. برای تعیین متغیر وابسته، از مدل قیمتگذاری اختیار معامله اروپایی (مدل BSM) استفاده شده و در نهایت با استفاده از مدل لاجیت چندجملهای و تعیین ارتباط بین متغیرهای مستقل و متغیر وابسته، مدل ترکیبی استخراج شده است.
یافتهها: یافتههای پژوهش حاکی از آن است که دقت پیشبینی مدل، مدل مرتون و مدل ترکیبی در گروه شرکتهای سالم، بهترتیب برابر با 100، 85 و 90 درصد است. برای گروه شرکتهای درحال درماندگی دقت پیشبینی بهترتیب 50، 85 و 85 درصد و در گروه شرکتهای درمانده، بهترتیب برابر با 95، 85 و 90 درصد برای سال مالی 98 بهدست آمد.
نتیجهگیری: بر اساس نتایج پژوهش، مدل آلتمن در مقایسه با مدلهای ترکیبی و مرتون، قدرت پیشبینی مناسبتری برای شرکتهای سالم و درمانده دارد؛ این در حالی است که برای پیشبینی شرکتهای در حال درماندگی، مدل مرتون و مدل ترکیبی در مقایسه با مدل آلتمن از عملکرد بهتری برخوردار بودند.
Objective: Financial distress, which is defined as the uncertainty about the company's ability to meet its obligations and repay its debts, has been estimated by different models divided into three groups of fundamental models (based on accounting or financial data), structural models (based on the company's capital structure or market information) and hybrid models. Accurately predicting financial distress is still a major point of challenge for financial researchers. Scholars acknowledge that financial distress will be experienced when it happens. Therefore, the best thing to do is to initially estimate the probability of a company's financial distress. In this regard, in the current study, first, a hybrid model was presented to investigate the ability of financial distress prediction models. Next, in order to compare the hybrid model with accounting-based models, the second version of Altman's Z model known as the Z˝ model was used. To compare the hybrid model with market-based models, Merton's model was used in three groups including healthy, distressing, and distressed companies. Methods: In this research, by reviewing past studies, 47 variables affecting financial distress, such as accounting variables, market variables, and macroeconomic indicators were identified. Afterward, considering the frequency and successful performance of these variables in past studies, 19 variables were selected. In the next step, using the Stepwise regression test, among the 19 variables, 10 variables with probability values smaller than 0.05 were chosen. Also, to determine the dependent variable, the European option pricing model (Merton's model) was used. Finally, by the use of the Multinomial logit model and identifying the relationship between the dependent and independent variables, the hybrid model for predicting financial distress was designed. In order to compare the produced hybrid model with accounting-based fundamental models, the second version of Altman's Z model known as the Z˝ model was used. To compare the hybrid model with market-based structural models, Merton's model was used. Moreover, in order to test the ability of financial distress prediction models, a sample including 100 companies listed on the Tehran Stock Exchange (TSE) or Iran FaraBourse (IFB) was selected. Then, considering the defined criteria, these companies were divided into three groups consisting of healthy, distressing, and distressed companies. Finally, the ability of the above-mentioned models in predicting financial distress was investigated. Results: Research findings indicated that in the hybrid model, the ratios of Net Working Capital to Total Assets (WCTA), Operating Cash Flow to Total Assets (OCTA), Sales to Total Assets (STA), Net Income to Total Assets (NITA), Short-term and Long-term Debts to Equity (TLTE), Price to Earnings Per Share (P/E) and Price to Sales (P/S), and the variable of Interest Rate (INT) had significant relations with company's financial distress probability. Also, a comparison of the hybrid model and conventional models revealed that in the group of financially distressed companies, respectively, the Z˝ model with 100% accuracy, Merton's model with 85% accuracy, and the hybrid model with 90% accuracy had correctly predicted the financial situation of the companies. While, in the group of financially distressing companies, the accuracy of the Z˝ model, Merton's model, and the hybrid model in predicting the financial situation of the companies, stood at 50%, 85%, and 85%, respectively. In addition, in the group of healthy companies, these models were able to correctly predict 95%, 85%, and 90% of the companies' financial situation, respectively. Conclusion: According to achieved results, the Z˝ model has higher predictive power on healthy and distressed companies, compared to the hybrid and Merton models. While, the hybrid and Merton models are better at predicting the financial situation of distressing companies than the Z˝ model. Therefore, considering that the performance of the market-based model of Merton in predicting the financial situation of the companies is weaker than those of the Z˝ and that the hybrid models which are mainly formed by financial or accounting ratios, and also in regard to the findings of past studies which proved the inefficiency of the stock market in Iran, it can be concluded that it is better to use accounting variables in future research in the field of predicting financial distress.
خلاصه ماشینی:
Hillegeist, Keating, Cram & Lundstedt 7.
بت شکن ، سليمي و فلاحتگر متحدجو (١٣٩٧) در تحقيق خود يک روش ترکيبي به منظور پيش بيني درماندگي مالي شرکت هاي پذيرفته شده در بورس اوراق بهادار تهران ارائه دادند.
مرحله ششم : آزمون صحت و دقت مدل هاي پيش بيني درماندگي مالي ترکيبي ، مرتون و Z آلـتمن بـراي هـر يـک از شرکت هاي منتخب پذيرفته شده در بورس اوراق بهادار تهران .
(به تصویر صفحه رجوع شود) نتيجه گيري و پيشنهادها با توجه به اهميت پيش بيني درماندگي مالي ، در پژوهش حاضر ضمن ارائه يک مدل ترکيبي ، به منظور مقايسه مدل مزبور با مدل هاي مبتني بر داده هاي حسابداري از نسخه دوم مدل Z آلتمن موسوم به مدل Z و براي مقايسه با مدل مبتني بـر بازار از مدل مرتون استفاده شده است .
Westerberg, Singh, Hackner & Hoonyoung 5.
ارائه يک روش ترکيبي به منظور پيش بيني درمانـدگي مالي شرکت هاي پذيرفته شده در بورس اوراق بهادار تهران .
استفاده از روش ترکيبي انتخاب ويژگـي پـي درپـي پيشـرو شـناور و ماشين بردار پشتيبان در پيش بيني درماندگي مالي شرکت هاي پذيرفته شده در بورس اوراق بهادار تهران .
Applying Combined Approach of Sequential Floating Forward Selection and Support Vector Machine to Predict Financial Distress of Listed Companies in Tehran Stock Exchange Market.
Predicting firm financial distress: A mixed Logit model, The Accounting Review, 79(4), 1011-1038.