“The Squawk Bot”The name of this work is inspired by the popular financial commentary show called “Squawk Box” on CNBC (CNBC. Squawk Box: Business, Politics, Investors and Traders, https://www.cnbc.com/squawk-box-us/ , accessed May 23rd, 2019): Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering
Table 4: News headlines from three days selected from the test set, along with the attention mass (annotated in the numeric columns) by: GRUtxt, LSTMw/o and MSIN. Colored headlines are relevant news outputted by our model based on setting the accumulated probability mass ≥50%.
['GRUtxt', 'LSTMw/o', 'MSIN', 'News headlines']
As observed, our model MSIN places more probability mass on the headlines whose contents directly report the market performance, while zeros out mass on headlines that report company-events or local markets. Its attention mass is also more condense, with clear focus on a small set of top relevant news, as compared to those of LSTMw/o and GRUtxt that both spread out on multiple headlines.