| Summary: | Being able to determine the financial outlook of a company is imperative for one to look for
investment opportunities. Three areas are identified which enable investors to better understand
the financial outlook of a company: financial statements, financial news, and financial reports.
As financial statements refer mainly to financial accounting information, critical information
can be displayed in a form of a dashboard. The business information, activities and operations are
mainly presented in the text found in 10-K reports. Extractive text summary methodology called
TextRank with Global Vectors for word representations (GloVe) would be used to find key
sentences in the report. Lastly, we would use sentiment classification on news articles to better
understand and consolidate the views of articles that may affect the public’s opinion of the
company. For sentiment classification, Vanilla RNN, LSTM, bidirectional LSTM, and different forms
of artificial Recurrent Neural Network (RNN) architecture would be explored. Transfer learning
would be applied with word embeddings by Word2Vec. The model with the best accuracy would
be used for the sentiment classification of company news.
The outputs are consolidated in a web application using React. This web application would display
the dashboard, the summary of financial reports, and the sentiment of news articles for each company.
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