This paper aims to develop a novel approach for predicting stock prices by leveraging sentiment analysis and deep learning techniques within a stochastic context. This approach aims to incorporate the impact of investor and market sentiment on stock prices, considering the inherent uncertainty and randomness in the financial markets.
In today's fast-paced and unpredictable financial markets, the ability to accurately predict stock prices is a highly sought-after skill. Traders and investors are constantly seeking innovative approaches to gain an edge and make informed decisions. One such approach that has gained significant attention is the use of sentiment analysis combined with machine learning techniques.
By analyzing social media sentiment, news articles, and other relevant data, researchers and analysts can uncover valuable insights into market trends and investor sentiment. Sentiment analysis involves the use of natural language processing and machine learning algorithms to determine the emotional tone of a piece of text.