📈 Stock Market Technical Indicator Analysis System

A real-time, web-based platform that helps traders and investors make data-driven decisions using a combination of widely used technical indicators. This system automates the fetching of stock data, calculates multiple indicators, and generates buy/sell/hold signals based on standard thresholds and custom user-defined strategies.

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🚀 Features

• Fetches real-time or daily stock data and stores it in PostgreSQL
• Calculates key technical indicators:
  • RSI (Relative Strength Index)
  • SMA (Simple Moving Average)
  • ADX (Average Directional Index)
  • OBV (On-Balance Volume)
  • Momentum
• Generates Bullish/Bearish/Neutral signals based on industry-standard rules
• Users can combine indicators with custom weightages to form personalized strategies
• Dynamic and responsive web interface with:
  • Table showing bullish/bearish indicator values
  • Company-specific technical insights
  • Interactive chart view with price and indicator overlays
• Scheduled backend processes for scraping and indicator calculation

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🌐 Live Demo

Note: This project was developed as a final year academic submission and is currently not deployed online.

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🛠️ Tech Stack

• Backend: Python, Flask
• Frontend: HTML, CSS, JavaScript (Fetch API)
• Database: PostgreSQL
• Scheduling: Cron / APScheduler (for automated scraping and calculations)
• Data Source: Custom scraper for daily stock data (due to lack of local APIs)
• Libraries Used:
  • pandas, numpy, sqlalchemy
  • Technical analysis functions (custom implementations or TA-Lib if supported)

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🧠 Key Concepts

• Multi-indicator analysis: Combine several indicators to reduce noise and improve signal clarity.
• Swing trading strategy: Signals designed to assist in short- to medium-term trading decisions.
• Real-time data pipeline: Backend fetches and analyzes stock data on schedule, making insights readily available.
• Custom signal generation: Combine indicator outputs with weightages to define your own strategies.

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📷 UI Overview

• Landing Page: Project introduction and navigation
• Core Page: Table view showing multiple companies and their bullish/bearish signals
• Company Page: Detailed view of indicator values and explanation
• Chart Popup: Interactive charts showing price and technical indicators over time

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📁 Folder Structure

.
├── database
│   ├── db_setup.py
│   ├── finddups.py
│   ├── insert_and_replace_merged_csv.py
│   ├── insert_company.py
│   ├── insert_data(all).py
│   ├── insert_each_csv.py
│   ├── insert_merged_data.py
│   ├── merge_csv.py
│   ├── stock_price_data_export.csv
│   ├── tocsv.py
│   └── venv
│       ├── bin
│       ├── include
│       ├── lib
│       ├── lib64 -> lib
│       ├── pyvenv.cfg
│       └── share
├── main_app
│   ├── app
│   │   ├── calculate_indicators.py
│   │   ├── calculations.py
│   │   ├── email_service.py
│   │   ├── __init__.py
│   │   ├── live_market
│   │   ├── models.py
│   │   ├── old_models.py
│   │   ├── old_routes.py
│   │   ├── __pycache__
│   │   ├── routes.py
│   │   ├── scraper.py
│   │   ├── static
│   │   └── templates
│   ├── checkkk.py
│   ├── config.py
│   ├── instance
│   ├── main.py
│   ├── migrations
│   │   ├── alembic.ini
│   │   ├── env.py
│   │   ├── __pycache__
│   │   ├── README
│   │   ├── script.py.mako
│   │   └── versions
│   ├── __pycache__
│   │   └── config.cpython-38.pyc
│   ├── requirements.txt
│   └── venv
│       ├── bin
│       ├── include
│       ├── lib
│       ├── lib64 -> lib
│       ├── pyvenv.cfg
│       └── share
└── scraping
    ├── README.md
    ├── stockscraper
    │   ├── scrapy.cfg
    │   └── stockscraper
    └── venv
        ├── bin
        ├── include
        ├── lib
        ├── lib64 -> lib
        ├── pyvenv.cfg
        └── share

📚 References

• TA-Lib & Python TA Libraries
• Academic research papers on trading strategies

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