Hybrid Market Trend Predictor With Event Alerts, Sentiment Visualization And Portfolio Recommendation

Abstract

Accurate forecasting is difficult due to the stock market's dynamic character, which is impacted by company events, investor emotion, and economic factors. In order to predict market movements, this study suggests a Hybrid Market Trend Predictor that combines sentiment research, technical indicators, and event-driven signals. Investors can compare trends across multiple equities at once thanks to the system's provision for multi-stock research. The framework also includes real-time event alerts to inform users of important geopolitical or financial developments that could affect stock performance. In order to offer intuitive insights into investor opinions gleaned from analyst reports, social media, and financial news, sentiment visualization is used. Additionally, the system provides portfolio suggestion tools that direct investors toward the best stock choices based on risk tolerance and predictive analytics. By integrating quantitative and qualitative data sources, the suggested hybrid strategy improves decision-making and produces more dependable investment strategies and forecasting accuracy.