Quant-Finance

Introduction

Welcome to 'Quantfinance with backtesting Strategies' - a comprehensive collection of over 200+ Python programs designed for quantitative finance enthusiasts and professionals. This repository is your go-to resource for gathering, manipulating, and analyzing stock market data, leveraging the power of Python to unlock insights in the financial markets.

Organization

Our repository is organized into several key sections:

find_stocks

Programs to screen stocks based on technical and fundamental analysis.

machine_learning

Introductory machine learning applications for stock classification and prediction.

portfolio_strategies

Simulations of trading strategies and portfolio analysis tools.

stock_analysis

Detailed analysis tools for individual stock assessment.

stock_data

Tools for collecting stock price action and company data via APIs and web scraping.

technical_indicators

Visual tools for popular technical indicators like Bollinger Bands, RSI, and MACD.

Installation

To get started, clone the repository and install the required dependencies:

git clone https://github.com/aditya-dom/Quantfinance-with-backtesting.git
cd Finance
pip install -r requirements.txt

Usage

Detailed instructions on how to use each program can be found within their respective directories. Explore different modules to discover their functionalities.

Each script in this collection is stand-alone. Here's how you can run a sample program:

python example_program.py

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

Authors

• @aditya-dom

License

This project is licensed under the MIT License.

Acknowledgements

• Stock_Analysis_For_Quant by LastAncientOne

Disclaimer

The material in this repository is for educational purposes only and should not be considered professional investment advice.