Rohit Beri

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Stock Return Prediction using Transfer Learning on Textual Data


Eduardo Peynetti


Rohit Beri


Jessica Wijaya


Stuart Neilson

This article was produced as part of the final project for

Harvard’s AC295 Fall 2020



Transfer Learning, combined with open-sourced state-of-the-art (SOTA) neural network models has democratized and hastened the adoption of machine learning in a variety of fields ranging from medical science to astronomy. In this article, we explore the applicability of SOTA Natural Language Processing models for sentiment analysis in the financial domain (news, press releases, 10-Ks) to build profitable trading strategies.

We explore three different models, Loughran-McDonald, BERT, and Fin-BERT. We fine-tune Fin-BERT and take a look…

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