I'm thrilled to introduce my latest project, a Stock Financial Assistant built using Python, Flask, and a suite of powerful libraries and APIs. This tool is designed to help investors.
Deployed link:-
https://obnoxious-erna-bfdfdgd-fc37455c.koyeb.app/
I'm thrilled to introduce my latest project, a ClarityTrade built using Python, Flask, and a suite of powerful libraries and APIs. This tool is designed to help investors make informed decisions by providing real-time stock predictions, technical analysis, and investment insights. Here's a breakdown of its key features:
Predictive Modeling: leveraging Random Forest Regression and technical indicators (like RSI, MACD, Moving Averages), the tool predicts future stock prices with high accuracy.
Historical Data Analysis: Fetches historical stock data using the Alpha Vantage API and trains the model to forecast prices.
AI-Powered Insights: Integrates with Google News API to fetch the latest stock-related news and uses Gemini AI to provide actionable investment recommendations.
Customizable Reports: Generates formatted investment decisions with bold text, bullet points, and HTML formatting for easy readability.
Plotly Charts: Displays interactive charts comparing predicted vs. actual stock prices over time.
Dynamic Updates: Visualizations are updated in real-time based on user inputs.
Secure Login: Users can register and log in securely with email verification and password protection.
Dynamic Updates: Visualizations are updated in real-time based on user inputs.
Holiday Detection: The tool checks for market holidays using the Holiday API to avoid making predictions on non-trading days.
AI Chatbot: Users can interact with a Gemini-powered chatbot to ask questions about their investment decisions or stock predictions. The chatbot provides context-aware responses and handles out-of-context queries gracefully.
Verification Codes: Sends email verification codes using SMTP for secure user authentication.
Custom Alerts: (Future feature) Plans to include email alerts for significant stock price changes or investment opportunities.
Flask Framework: Built using Flask for a lightweight and scalable web application.
Modular Code: The codebase is modular, making it easy to add new features or integrate additional APIs.
GitHub Repository: The project is open-source, allowing developers to contribute, extend, or customize it for their needs.
This project combines data science, web development, and AI to create a powerful tool for investors. Whether you're a beginner or an experienced trader, this assistant can help you make smarter investment decisions with confidence.
1. Data Retravel 2. data pre processing 3. Random Forest regressor 4. Frontend Design 5. Chatbot Integration