Proceedings of the 2012 National Conference on Information Technology and Computer Science

Application of Optimized Combination Method to Financial Risk Forecasting for Listed Companies

Authors
Shuang Zhang, Qing-he Hu
Corresponding Author
Shuang Zhang
Available Online November 2012.
DOI
10.2991/citcs.2012.71How to use a DOI?
Keywords
financial risk; forecasting; combination forecast model; ant colony algorithm
Abstract

In a market economy, the competition among enterprises is becoming fiercer. Examples of declaring bankruptcy have become common. Financial risk is predictable, so it is of great practical significance for listed enterprises and the stakeholders to establish an effective financial risk forecasting model. The paper establishes a combination forecast model optimized with ant colony algorithm, to overcome the limitations of single model forecast, based on listed enterprises situation and characters and knowledge of economy management and accounting. It solves the problem of determining weight, and screens out better single forecast model. In this way, forecast content are more comprehensive.

Copyright
© 2012, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2012 National Conference on Information Technology and Computer Science
Series
Advances in Intelligent Systems Research
Publication Date
November 2012
ISBN
10.2991/citcs.2012.71
ISSN
1951-6851
DOI
10.2991/citcs.2012.71How to use a DOI?
Copyright
© 2012, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Shuang Zhang
AU  - Qing-he Hu
PY  - 2012/11
DA  - 2012/11
TI  - Application of Optimized Combination Method to Financial Risk Forecasting for Listed Companies
BT  - Proceedings of the 2012 National Conference on Information Technology and Computer Science
PB  - Atlantis Press
SP  - 268
EP  - 271
SN  - 1951-6851
UR  - https://doi.org/10.2991/citcs.2012.71
DO  - 10.2991/citcs.2012.71
ID  - Zhang2012/11
ER  -