#NIFTY50-Analysis

This repository contains code for exploring, analyzing, and predicting trends in the NIFTY 50 Index, India's benchmark stock market index. The analysis includes the calculation of various technical indicators such as moving averages, MACD, RSI, and Bollinger Bands, as well as the development and evaluation of predictive models using linear regression and artificial neural networks.

Contents

Introduction Setup Analysis Predictive Modeling Visualizations Usage Contributing License Introduction

Stock market analysis is crucial for investors and traders to make informed decisions. This project focuses on analyzing the NIFTY 50 Index, a key indicator of the Indian stock market, using various technical analysis techniques and machine learning models.

Setup

To run the code in this repository, follow these steps:

Clone the repository: bash Copy code git clone https://github.com/ArihanSinha08/NIFTY50-Analysis.git Install the required dependencies: bash Copy code pip install -r requirements.txt Run the analysis scripts: bash Copy code python analysis.py Analysis

The analysis script performs the following tasks:

Reads historical data of the NIFTY 50 Index from a CSV file. Calculates moving averages, MACD, RSI, and Bollinger Bands. Visualizes the calculated indicators using matplotlib. Predictive Modeling

The predictive modeling script builds and evaluates machine learning models for predicting future stock prices based on historical data and technical indicators.

Visualizations

The repository includes visualizations generated from the analysis, covering various aspects of the NIFTY 50 Index, including time series plots, moving averages, MACD, RSI, and Bollinger Bands.

Usage

Feel free to use the code in this repository for your analysis or modify it according to your requirements. If you find any issues or have suggestions for improvement, please open an issue or submit a pull request.

Contributing

Contributions are welcome! If you'd like to contribute to this project, please follow these steps:

Fork the repository. Create a new branch (git checkout -b feature/improvement). Make your changes. Commit your changes (git commit -am 'Add new feature'). Push to the branch (git push origin feature/improvement). Create a new Pull Request. License

This project is licensed under the MIT License - see the LICENSE file for details.