Authors: Richard Heuver 1 and Ron Triepels 2

Affiliations: 1 De Nederlandsche Bank, Amsterdam and The Netherlands ; 2 De Nederlandsche Bank, Amsterdam, The Netherlands, Tilburg University, Tilburg and The Netherlands

ISBN: 978-989-758-350-6

Keyword(s): Liquidity Stress, Risk Monitoring, Financial Market Infrastructures, Large-value Payment Systems.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial Applications of AI ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems ; Theory and Methods

Abstract: Liquidity stress constitutes an ongoing threat to financial stability in the banking sector. A bank that manages its liquidity inadequately might find itself unable to meet its payment obligations. These liquidity issues, in turn, can negatively impact the liquidity position of many other banks due to contagion effects. For this reason, central banks carefully monitor the payment activities of banks in financial market infrastructures and try to detect early-warning signs of liquidity stress. In this paper, we investigate whether this monitoring task can be performed by supervised machine learning. We construct probabilistic classifiers that estimate the probability that a bank faces liquidity stress. The classifiers are trained on a dataset consisting of various payment features of European banks and which spans several known stress events. Our experimental results show that the classifiers detect the periods in which the banks faced liquidity stress reasonably well.

PDF ImageFull Text


Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Heuver, R. and Triepels, R. (2019). Liquidity Stress Detection in the European Banking Sector.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-350-6, pages 266-274. DOI: 10.5220/0007395602660274

author={Richard Heuver. and Ron Triepels.},
title={Liquidity Stress Detection in the European Banking Sector},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},


JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Liquidity Stress Detection in the European Banking Sector
SN - 978-989-758-350-6
AU - Heuver, R.
AU - Triepels, R.
PY - 2019
SP - 266
EP - 274
DO - 10.5220/0007395602660274

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.