An overview of stock trading with sentiment analysis

This study investigates how sentiment analysis, using advanced Natural Language Processing (NLP) techniques, can predict stock market trends, specifically examining Boeing stock (ticker: BA) over three months. Utilising multiple sentiment analysis models like Sentic API, TextBlob, VADER, BERT, and F...

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Main Author: Tang, Yi Qwan
Other Authors: Erik Cambria
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/175215
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1752152024-04-26T15:41:39Z An overview of stock trading with sentiment analysis Tang, Yi Qwan Erik Cambria Patrick Pun Chi Seng School of Computer Science and Engineering cambria@ntu.edu.sg, cspun@ntu.edu.sg Computer and Information Science Trading Sentiment analysis Stock Finance Natural language processing This study investigates how sentiment analysis, using advanced Natural Language Processing (NLP) techniques, can predict stock market trends, specifically examining Boeing stock (ticker: BA) over three months. Utilising multiple sentiment analysis models like Sentic API, TextBlob, VADER, BERT, and FinBERT, alongside varying preprocessing methods and news formats, the research explores optimal trading signals for high-frequency trading. The findings indicate that FinBERT, tailored for the financial sector, significantly outperforms other models, achieving up to a 63% return on investment. Results show that preprocessing techniques like stop word removal and lemmatisation do not significantly impact performance, while trading signals derived from full news content and summaries yield better results than those from headlines alone. The study challenges the Efficient Market Hypothesis by using random strategies as benchmarks, demonstrating that sentiment-driven strategies can exploit market inefficiencies to generate superior returns. Bachelor's degree 2024-04-21T11:27:21Z 2024-04-21T11:27:21Z 2024 Final Year Project (FYP) Tang, Y. Q. (2024). An overview of stock trading with sentiment analysis. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175215 https://hdl.handle.net/10356/175215 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
Trading
Sentiment analysis
Stock
Finance
Natural language processing
spellingShingle Computer and Information Science
Trading
Sentiment analysis
Stock
Finance
Natural language processing
Tang, Yi Qwan
An overview of stock trading with sentiment analysis
description This study investigates how sentiment analysis, using advanced Natural Language Processing (NLP) techniques, can predict stock market trends, specifically examining Boeing stock (ticker: BA) over three months. Utilising multiple sentiment analysis models like Sentic API, TextBlob, VADER, BERT, and FinBERT, alongside varying preprocessing methods and news formats, the research explores optimal trading signals for high-frequency trading. The findings indicate that FinBERT, tailored for the financial sector, significantly outperforms other models, achieving up to a 63% return on investment. Results show that preprocessing techniques like stop word removal and lemmatisation do not significantly impact performance, while trading signals derived from full news content and summaries yield better results than those from headlines alone. The study challenges the Efficient Market Hypothesis by using random strategies as benchmarks, demonstrating that sentiment-driven strategies can exploit market inefficiencies to generate superior returns.
author2 Erik Cambria
author_facet Erik Cambria
Tang, Yi Qwan
format Final Year Project
author Tang, Yi Qwan
author_sort Tang, Yi Qwan
title An overview of stock trading with sentiment analysis
title_short An overview of stock trading with sentiment analysis
title_full An overview of stock trading with sentiment analysis
title_fullStr An overview of stock trading with sentiment analysis
title_full_unstemmed An overview of stock trading with sentiment analysis
title_sort overview of stock trading with sentiment analysis
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/175215
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