Mapping interest rate projections using neural networks under cointegration
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
Authors
This paper discusses the application of techniques of business analytics in the banking industry examining stress tests in the context of financial risk management. We focus on the use of neural networks in combination with techniques of cointegration analysis to map swap rate projections derived from given scenarios (e.g., a certain stress scenario from the EBA/ECB 2016 EU-wide stress test) on other relevant interest rates in order to ensure that contingent projections for these time series are produced and used in the process of stress testing.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the International Conference on Internet of Things and Machine Learning, IML 2017 |
| Editors | Hani Hamdan, Faouzi Hidoussi, Djallel Eddine Boubiche |
| Number of pages | 5 |
| Publisher | Association for Computing Machinery, Inc |
| Publication date | 17.10.2017 |
| Article number | a13 |
| ISBN (electronic) | 9781450352437 |
| DOIs | |
| Publication status | Published - 17.10.2017 |
| Externally published | Yes |
| Event | 1st International Conference on Internet of Things and Machine Learning - IML 2017 - John Moores University, Liverpool, United Kingdom Duration: 17.10.2017 → 18.10.2017 Conference number: 1 |
- Artificial neural networks, Cointegration, Mapping interest rate projections, Net interest rate income, Risk management
- Management studies