Skip to content

shrvan30/Stock_Market_Trend_Analyzer_using_Moving_Averages_and_Machine_Learning

Repository files navigation

Stock_Market_Trend_Analyzer_using_Moving_Averages_and_Machine_Learning

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

📈 Stock Price Predictor using Moving Averages & Machine Learning

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.


🔧 Features

  • ✅ 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

📦 Tech Stack

  • Python 3.10+
  • Streamlit
  • yFinance
  • scikit-learn
  • pandas, numpy
  • TensorFlow/Keras
  • Matplotlib

About

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

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors