|Publication type:||Conference other|
|Type of review:||Peer review (abstract)|
|Title:||Predicting investor behaviour in European bond markets : a machine-learning approach|
|Conference details:||4th European Conference on Artificial Intelligence in Finance and Industry, Winterthur, Switzerland, 5 September 2019|
|Subject (DDC):||006: Special computer methods |
|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.|
|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|
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