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Title: Consolidating financial outlook of companies
Authors: Ting, Irvin Sie Ze
Keywords: Engineering::Computer science and engineering::Software::Software engineering
Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Ting, I. S. Z. (2022). Consolidating financial outlook of companies. Final Year Project (FYP), Nanyang Technological University, Singapore.
Project: SCSE21-0162
Abstract: 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.
Schools: School of Computer Science and Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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