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دسته بندی:
یادگیری عمیق - deep learning
سال انتشار:
2019
عنوان انگلیسی مقاله:
Deep learning models for bankruptcy prediction using textual disclosures
ترجمه فارسی عنوان مقاله:
مدل های یادگیری عمیق برای پیش بینی ورشکستگی با استفاده از افشای متن
منبع:
Sciencedirect - Elsevier - European Journal of Operational Research, 274 (2018) 743-758: doi:10:1016/j:ejor:2018:10:024
نویسنده:
Feng Mai a , ∗, Shaonan Tian b , Chihoon Lee a , Ling Ma a
چکیده انگلیسی:
This study introduces deep learning models for corporate bankruptcy forecasting using textual disclo- sures. Although textual data are common, it is rarely considered in the financial decision support models. Deep learning uses layers of neural networks to extract features from textual data for prediction. We con- struct a comprehensive bankruptcy database of 11,827 U.S. public companies and show that deep learning models yield superior prediction performance in forecasting bankruptcy using textual disclosures. When textual data are used in conjunction with traditional accounting-based ratio and market-based variables, deep learning models can further improve the prediction accuracy. We also investigate the effectiveness of two deep learning architectures. Interestingly, our empirical results show that simpler models such as averaging embedding are more effective than convolutional neural networks. Our results provide the first large-sample evidence for the predictive power of textual disclosures.
Keywords: Decision support systems | Deep learning | Bankruptcy prediction | Machine learning | Textual data
قیمت: رایگان
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