📈 Algotrading With Sentiment Analysis

A real-time stock price monitoring and prediction pipeline built with Python, designed for high-frequency trading and dynamic financial analysis using machine learning techniques and sentiment-driven insights.

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🚀 Features

• 📊 Real-time Stock Data Collection using the Yahoo Finance API (yfinance)

• 🧹 Data Preprocessing with datetime formatting, missing-value handling, normalization

• 🧠 Ready for ML Model Integration (LSTM, XGBoost, Linear Regression)

• 🧱 Modular Design for ease of testing, scaling, and extension

• 💾 Data Saving as clean CSVs for downstream analytics

• 📉 Exploratory Analysis: Trend visualization, volatility, technical indicators

• 📦 Two working notebooks:

  • 5stocks.ipynb – fetches and processes multiple stock data
  • marketstocks.ipynb – customizable real-time stock data pipeline

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📂 Project Structure

.
├── 5stocks.ipynb
├── marketstocks.ipynb
├── GenAI_Report_Group_9.pdf  # Detailed project report
├── requirements.txt
└── README.md

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🏗️ Pipeline Components

Function	Description
get_live_stock_data()	Fetches OHLCV data from Yahoo Finance
preprocess_data()	Cleans data: datetime conversion, missing value treatment, etc.
save_data()	Saves cleaned data to CSV
run_pipeline()	Orchestrates full flow: fetch → preprocess → save

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📈 Exploratory Analysis Examples

• 📍 Trend & volatility plots (OHLC, rolling std deviation)
• 🔁 Technical indicators like RSI, MACD, Moving Averages
• 📌 Correlation heatmaps
• 📦 Histogram and distribution plots for returns

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📚 Future Enhancements

• 🤖 Integrate ML models like LSTM or XGBoost for forecasting
• 📊 Build interactive dashboards with Streamlit or Dash
• 🔔 Real-time alerts for trade signals or major price shifts
• 💬 Integrate news sentiment analysis for smarter predictions

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🔧 Installation & Setup

git clone https://github.com/Anshul-ydv/Algo_trader_with_sentiment.git
cd Algotrading-Sentiment
pip install -r requirements.txt

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📋 Usage

In marketstocks.ipynb, change:

ticker = 'TCS.NS'
interval = '1d'

Run the pipeline:

run_pipeline(ticker, interval, save_path='TCS_cleaned.csv')

To analyze multiple stocks, use 5stocks.ipynb.

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📄 Report

For complete methodology, literature review, and diagrams, see [Report.pdf).

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📜 License

This project is licensed under the MIT License.