Forecast the future. Analyze the past. Make smarter decisions.
Stocklyzer is a real-time stock analysis web app built using Streamlit, empowering users to visualize stock trends, evaluate performance, and predict future prices using financial models like CAPM and ARIMA. Ideal for retail investors, analysts, and students.
- Calculate Beta and Expected Returns
- Analyze stock risk vs market
- Interactive price performance charts
- Technical indicators
- Volume and trend analysis
- Moving averages & historical insights
- Forecast next 30 days using ARIMA
- Interactive charts of predicted vs historical prices
- Search by stock ticker or company name
- Frontend / App Interface: Streamlit
- Data Sources: yFinance, NumPy, Pandas
- Modeling: ARIMA (statsmodels)
- Visualization: Matplotlib, Plotly
- Deployment: Streamlit Cloud
Hi, I’m Akash Parley — a data enthusiast passionate about building intelligent, user-friendly analytics tools.
📬 Reach out: akashparle786@gmail.com
🔗 Connect on LinkedIn
💻 Explore more on GitHub
If you found this project helpful or inspiring, feel free to ⭐ star the repo and reach out!
# Clone the repository
git clone https://github.com/AkashParley/Stocklyzer.git
# Navigate to the project folder
cd Stocklyzer
# Install dependencies
pip install -r requirements.txt
# Run the Streamlit app
streamlit run stock_app.py