|Publication type:||Conference other|
|Type of review:||No review|
|Title:||Correlation influence networks for sentiment analysis in European sovereign bonds|
|Authors :||Schwendner, Peter|
|et. al :||No|
|Conference details:||Financial Revolution - Sentiment Analysis, AI and Machine Learning, Zürich, Switzerland, 30 October 2018|
|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.|
|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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