2024/09/30 by Fabian Billert, Stefan Conrad, Billert, Fabian +1
Computer Science · #Advanced Text Analysis Techniques #Data Visualization and Analytics
paper · pdf · doi:10.48550/arxiv.2409.20397
We extract the sentiment from german and english news articles on companies in the DAX40 stock market index and use it to create a sentiment-powered pendant. Comparing it to existing products which adjust their weights at pre-defined dates once per month, we show that our index is able to react more swiftly to sentiment information mined from online news. Over the nearly 6 years we considered, the sentiment index manages to create an annualized return of 7.51% compared to the 2.13% of the DAX40, while taking transaction costs into account. In this work, we present the framework we employed to develop this sentiment index.