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arXiv · 2109.14394

EDGAR-CORPUS: Billions of Tokens Make The World Go Round

Lefteris Loukas·Manos Fergadiotis·Ion Androutsopoulos·Prodromos Malakasiotis
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Abstract

We release EDGAR-CORPUS, a novel corpus comprising annual reports from all the publicly traded companies in the US spanning a period of more than 25 years. To the best of our knowledge, EDGAR-CORPUS is the largest financial NLP corpus available to date. All the reports are downloaded, split into their corresponding items (sections), and provided in a clean, easy-to-use JSON format. We use EDGAR-CORPUS to train and release EDGAR-W2V, which are WORD2VEC embeddings for the financial domain. We employ these embeddings in a battery of financial NLP tasks and showcase their superiority over generic GloVe embeddings and other existing financial word embeddings. We also open-source EDGAR-CRAWLER, a toolkit that facilitates downloading and extracting future annual reports.

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Lefteris Loukas, Manos Fergadiotis, Ion Androutsopoulos, Prodromos Malakasiotis. 2021-09-29. EDGAR-CORPUS: Billions of Tokens Make The World Go Round. https://doi.org/10.18653/v1/2021.econlp-1.2

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