| Publication type: | Conference other |
| Type of review: | Peer review (abstract) |
| Title: | Predicting investor behaviour in European bond markets : a machine-learning approach |
| Authors: | Hillebrand, Martin Schwendner, Peter Winant, Bastien Mravlak, Marko |
| et. al: | No |
| Conference details: | 4th European Conference on Artificial Intelligence in Finance and Industry, Winterthur, Switzerland, 5 September 2019 |
| Issue Date: | 5-Sep-2019 |
| Language: | English |
| Subject (DDC): | 006: Special computer methods 332.6: Investment |
| Abstract: | The European Rescue Fund ESM has, in its role as financial backstop of the Euro area, a specific interest in a comprehensive understanding of investor behaviour in order to ensure a stable and broad market access. With numerous transaction data as well as market and macro variables, a learning machine has been trained that forecasts investor demand in syndicated transactions. Out-of-sample tests show already a decent predictive power which is intended to be further improved by intelligent methods of data enhance-ment. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/20832 |
| Fulltext version: | Published version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Management and Law |
| Appears in collections: | Publikationen School of Management and Law |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.