/Python-For-Quants

Primary LanguageJupyter Notebook

Introduction to Python for Quants

This repository provides a foundational introduction to Python tailored for quantitative analysts and researchers (quants). Each section is demonstrated with Python code examples to help users understand and apply the concepts in practice.

Table of Contents

  1. Basic Python Concepts

    • Learn about variables, data types, operators, control structures, and functions.
    • View Code

  2. Advanced Python Concepts

    • Dive into classes, objects, modules, packages, and exception handling.
    • View Code

  3. NumPy for Quants

    • Understand array creation, mathematical operations, and statistical functions using NumPy.
    • View Code

  4. Pandas for Quants

    • Explore Series, DataFrames, data cleaning, and time-series analysis using Pandas.
    • View Code

  5. Data Visualization

    • Discover basic plotting with Matplotlib and advanced visualizations with Seaborn.
    • View Code

  6. Financial Libraries

    • Get introduced to popular financial libraries like QuantLib and Pyfolio.
    • View Code

  7. Monte Carlo Simulations

    • Understand the basics of Monte Carlo and its applications in finance.
    • View Code

  8. Time-Series Analysis

    • Delve into time series forecasting using models like ARIMA.
    • View Code

Getting Started

  1. Clone the repository.
  2. Ensure you have Python and the necessary libraries installed.
  3. Navigate to the desired section and run the corresponding Python file to see the concepts in action.

Contributions

Feel free to fork the repository, make changes, and submit pull requests. Feedback and improvements are always welcome!