"The Squawk Bot": Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering

Understand

Multimodal analysis that uses numerical time series and textual corpora as input data sources is becoming a promising approach, especially in the financial industry.

• However, the main focus of such analysis has been on achieving high prediction accuracy while little effort has been spent on the important task of understanding the association between the two data modalities.
• Performance on the time series hence receives little explanation though human-understandable textual information is available.
• In this work, we address the problem of given a numerical time series, and a general corpus of textual stories collected in the same period of the time series, the task is to timely discover a succinct set of textual stories associated with that time series.