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Certificate of Completion

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THIS ACKNOWLEDGES THAT

HAS COMPLETED THE MAY-SUMMER 2024 DATA SCIENCE BOOT CAMP

Ogonnaya Romanus

Roman Holowinsky, PhD

JUNE 10, 2024

DIRECTOR

DATE

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TEAM

Headlines and Market Trends: A Sentiment Analysis Approach to Stock Prediction

Jem Guhit, Sarasi Jayasekara, Nawaz Sultani, Timothy Alland, Ogonnaya Romanus, Kenneth Anderson

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Financial markets are often affected by sentiment conveyed in news headlines. As major news events can drive significant fluctuations in stock prices, understanding these sentiment trends can provide important insights into market movements. This project aims to answer the question whether the sentiments extracted from financial news headlines can predict stock movements.

We use 5 years worth of data extracted from Yahoo Finance and Stock News API, obtain sentiment scores using FinVader, and use Models: Logistic Regression, Gradient Boosted Trees, XGBoost, and LSTM, to predict whether the next day's stock prices would rise or fall. We use a simulated stock portfolio to evaluate the effectiveness of the models.

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