Algorithmic Trading and Quantitative Analysis of Indian Stock Market

Note: This project is for educational purposes only. Please do not make any financial decisions based on the code in this repository. Always consult with a financial expert before making any investment decisions.

This is a repository for implementing various algorithmic trading and quantitative analysis techniques for the Indian Stock Market using Python. It includes a variety of strategies ranging from simple moving averages to more advanced techniques like machine learning-based algorithms.

Table of Contents

• Introduction
• Features
• Installation
• Usage
• Contributing
• License

Introduction

Algorithmic trading involves the use of computer programs to automate trading decisions. These programs can be used to execute trades based on specific criteria such as price movements, market trends, and other factors. Quantitative analysis, on the other hand, involves the use of mathematical and statistical techniques to analyze market data and make trading decisions based on that analysis.

This repository aims to provide a collection of algorithmic trading and quantitative analysis techniques that can be used to analyze and trade the Indian stock market.

Features

This repository includes various features such as:

• Simple Moving Average (SMA) strategy
• Exponential Moving Average (EMA) strategy
• Buy and Hold Strategy
• Data visualization using Matplotlib and Seaborn

Installation

To use this repository, you must have Python 3.x installed on your system. To install the required packages, run the following command:

pip install -r requirements.txt

Usage

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

1. Clone this repository to your local machine.

2. Open a terminal and navigate to the repository's root folder.

3. Launch Jupyter Notebook using the following command :

jupyter notebook

4. Locate the fild and Run the .ipynb file

This will generate a visualization of the strategy along with the buy and sell signals.

Contributing

Contributions to this repository are always welcome. If you have any suggestions or improvements, please feel free to submit a pull request or open an issue.

License

This repository is licensed under the MIT license. See LICENSE for more information.