Publications:Predicting trends of financial attributes by an adaptive committee of models
From ISLAB/CAISR
| Title | Predicting trends of financial attributes by an adaptive committee of models |
|---|---|
| Author | Zivile Kalsyte and Antanas Verikas and Asta Vasiliauskaite |
| Year | 2012 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | Proceedings of the 7th International Conference on Electrical and Control Technologies ECT 2012 |
| Conference | The 7th International Conference on Electrical and Control Technologies, ECT-2012, Kaunas, Lithuania, May 3-4, 2012 |
| DOI | |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:548327 |
| Abstract | This paper presents an approach to designing an adaptive, data dependent, committee of multilayer perceptrons (MLP) for predicting trends (positive or negative change) of five financial attributes used for assessing future performance of a company. Total Asset Turnover (TAT), Current Ratio (CR), Gross Margin (GM), Operating Margin (OM), and Return on Equity (ROE) are the attributes used in this paper. A two- and three-years ahead prediction of change is considered. A Self-Organizing Map (SOM) used for data mapping and analysis enables building committees, which are specific (committee size and aggregation parameters) for each data point analyzed. When tested on data concerning 59 companies of the United States biotechnology sector, committees built according to the proposed technique outperformed both averaging and weighted averaging committees. |
