Stock Price Prediction Using Sentiment and Technical Analysis

With the rapid advancement of the economy, the stock market has garnered extensive attention in both business and academic fields. Due to the dynamic, unstable, information-sensitive nature of the stock market, obtaining an accurate stock price prediction is extremely challenging. This study explores the integration of sentiment data from financial news headlines with historical stock data to predict stock prices. This research gathered historical price and trading volume data for the S&P 500 index, sourced from Yahoo Finance, along with 106,494 financial news titles obtained from Reuter. This dataset encompasses the period around the 2008 financial crisis from Oct 20, 2006, to Nov 19, 2013. Empirical implementation of the proposed methodology revealed the substantial value of incorporating sentiment and historical information to enhance the accuracy of stock price prediction.