Fetches 20 years of stock data by default and allows users to modify the date range interactively, enabling flexible analysis of long-term or short-term market trends using Streamlit UI
This is a Streamlit-based web application that predicts stock prices using historical market data and machine learning models, particularly LSTM and Random Forest. It also visualizes Simple Moving Averages (SMA) over 100, 200, and 250 days for trend analysis and long-term investment strategies.
- ✅ Fetches 20 years of historical stock data via Yahoo Finance API
- ✅ Calculates and visualizes SMA (100, 200, 250 days)
- ✅ Compares SMA crossovers to detect buy/sell signals
- ✅ Predicts future stock trends using a trained ML model (
.keras) - ✅ Interactive charts & UI built with Streamlit
- Python 3.10+
- Streamlit
- yFinance
- scikit-learn
- pandas, numpy
- TensorFlow/Keras
- Matplotlib