Stock Market Next Day Forecast Data for

Stock market forecasting remains a complex and challenging task to forecast, traditional technical analysis methods such as RSI, EMA, and Candlestick Patterns often fail to analyze the stock market time series pattern with many recent studies now exploring forecasting using machine learning or neural networks, other studies have improved accuracy or decreased regression losses by applying technical indicators and sentiment analysis. This dataset aims to be used to analyze the performance of machine learning models in predicting the next day's stock market trend by combining technical and sentiment-based features. The technical indicators are derived from historical price data focusing on swing trends in the market and sentiment features are extracted using FinBERT from Benzinga Pro as a reliable financial news source. There are limitations to the dataset especially financial news articles. Limitations such as the availability of news data remain a major challenge that has the potential to improve the performance of a machine learning model.