| Publication type: | Conference other |
| Type of review: | No review |
| Title: | Correlation influence networks for sentiment analysis in European sovereign bonds |
| Authors: | Schwendner, Peter Schüle, Martin Hillebrand, Martin |
| et. al: | No |
| Conference details: | Financial Revolution - Sentiment Analysis, AI and Machine Learning, Zürich, Switzerland, 30 October 2018 |
| Issue Date: | 2018 |
| Language: | English |
| Subject (DDC): | 332.6: Investment |
| Abstract: | European sovereign bonds are especially sensitive to the political news flow. Consistent to the current sentiment, market makers adjust factor models in their quotation systems to be prepared for short-term market reactions in the most liquid instruments. We present a correlation influence network case study to make the signs of these factor betas transparent using intraday data analysis. This shows the sentiment of the most active market participants. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/17837 |
| Fulltext version: | Published version |
| License (according to publishing contract): | Licence according to publishing contract |
| Departement: | School of Management and Law |
| Organisational Unit: | Institute of Wealth & Asset Management (IWA) |
| Appears in collections: | Publikationen School of Management and Law |
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