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A Novel Soft Ensemble Model for Financial Distress Prediction with Different Sample Sizes
Joint Authors
Xu, Wei
Pan, Yuchen
Fu, Hong-Yong
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-04
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This work presents a novel soft ensemble model (ANSEM) for financial distress prediction with different sample sizes.
It integrates qualitative classifiers (expert system method, ES) and quantitative classifiers (convolutional neural network, CNN) based on the uni-int decision making method of soft set theory (UI).
We introduce internet searches indices as new variables for financial distress prediction.
By constructing a soft set representation of each classifier and then using the optimal decision on soft sets to identify the financial status of firms, ANSEM inherits advantages of ES, CNN, and UI.
Empirical experiments with the real data set of Chinese listed firms demonstrate that the proposed ANSEM has superior predicting performance for financial distress on accuracy and stability with different sample sizes.
Further discussions also show that internet searches indices can offer additional information to improve predicting performance.
American Psychological Association (APA)
Xu, Wei& Fu, Hong-Yong& Pan, Yuchen. 2019. A Novel Soft Ensemble Model for Financial Distress Prediction with Different Sample Sizes. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1195016
Modern Language Association (MLA)
Xu, Wei…[et al.]. A Novel Soft Ensemble Model for Financial Distress Prediction with Different Sample Sizes. Mathematical Problems in Engineering No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1195016
American Medical Association (AMA)
Xu, Wei& Fu, Hong-Yong& Pan, Yuchen. A Novel Soft Ensemble Model for Financial Distress Prediction with Different Sample Sizes. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1195016
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195016