Automatically Generating Macro Research Reports from a Piece of News
This addresses the time-sensitive need for macro analysts to draft reports quickly after news releases, though it appears incremental as it builds on existing long text generation techniques.
The paper tackles the problem of automatically generating macro research reports from economic news to save manual cost for analysts, proposing a deep learning approach with outline and report generation components and evaluating it on a crawled dataset with subjective assessment.
Automatically generating macro research reports from economic news is an important yet challenging task. As we all know, it requires the macro analysts to write such reports within a short period of time after the important economic news are released. This motivates our work, i.e., using AI techniques to save manual cost. The goal of the proposed system is to generate macro research reports as the draft for macro analysts. Essentially, the core challenge is the long text generation issue. To address this issue, we propose a novel deep learning technique based approach which includes two components, i.e., outline generation and macro research report generation.For the model performance evaluation, we first crawl a large news-to-report dataset and then evaluate our approach on this dataset, and the generated reports are given for the subjective evaluation.