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An open source, hands-on and fully reproducible book in quantitative finance, data science and econophysics. Join us and help Make Wall Street Great Again!

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README.md

The Open Quant Live Book Initiative

star this repo fork this repo License: CC BY-NC-SA 4.0 The Open Quant Book

Description

The book aims to be an Open Source introductory reference of the most important aspects of financial data analysis, algo trading, portfolio selection, econophysics and machine learning in finance with an emphasis in reproducibility and openness not to be found in most other typical Wall Street-like references.

Contribute

The Book is Open and we welcome co-authors. Feel free to reach out or simply create a pull request with your contribution! See project structure, guidelines and how to contribute here.

Working Contents

  1. The Basics
  • Free Data for Markets
  • Stylized Facts
  1. Algo Trading
  • Investment Process
  • Backtesting
  • Trading Strategies
  • Factor Investing
  • Limit Order
  1. Portfolio Optimization
  • Convex Optimization
  • Risk Parity Portfolios
  1. Machine Learning
  • Intro
  • Agent-Based Models
  • Binary Classifiers
  • Reinforcement Learning
  • Deep Learning
  • Hierarchical Risk Parity
  • AutoML
  1. Econophysics
  • Entropy, Efficiency and Bubbles
  • Nonparametric Statistical Causality: An Information-Theoretical Approach
  • Fractals and Scaling Laws
  • Financial Networks
  1. Alternative Data
  • The Market, The Players, The Rules
  • Case Studies

Book's information

Website: http://www.openquants.com/.

Licensed under Attribution-NonCommercial-ShareAlike 4.0 International.

Copyright (c) 2019. OpenQuants.com, New York, NY.