Hierarchical Model for Goal Guided Summarization of Annual Financial Reports

Agrawal, Y and Anand, V and Arunachalam, S and Varma, V (2021) Hierarchical Model for Goal Guided Summarization of Annual Financial Reports. In: WWW '21: The Web Conference 2021.

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Every year publicly listed companies file financial reports to give insights about their activities. These reports are meant for shareholders or general public to evaluate the company’s health and decide whether to buy or sell stakes in the company. However, these annual financial reports tend to be long, and it is time-consuming to go through the reports for each company. We propose a Goal Guided Summarization technique through which the summary is extracted. The goal, in our case, is the decision to buy or sell company’s shares. We use hierarchical neural models for achieving this goal while extracting summaries. By the means of intrinsic and extrinsic evaluation we observe that the summaries extracted by our approach can model the decision of buying and selling shares better compared to summaries extracted by other summarization techniques as well as the complete document itself. We also observe that the summary extractor model can be used to construct stock portfolios which give better returns compared to major stock index.

Item Type: Conference or Workshop Item (Paper)
Subjects: Marketing
Date Deposited: 16 Nov 2023 05:08
Last Modified: 16 Nov 2023 05:08
URI: https://eprints.exchange.isb.edu/id/eprint/2171

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