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

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