THE OPEN QUANT LIVE BOOK INITIATIVE
Publication Date: March, 2020.
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Are you tired of the lack of transparency and reproducibility in Wall Street? Are you frustrated by the highly-complex no-hands-on approaches from the traditional outdated Quant references?
The book aims to be an Open Source gentle introduction 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 references.
The Book is open and we welcome co-authors and collaborators, so visit our Github project and contribute!
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Table of Contents
Part I: Free Data for Markets
Chapter 1 Free Data for Markets
Chapter 2 Stylized Facts
Chapter 3 Correlation & Causation
Part II: Algo Trading
Chapter 4 Investment Process
Chapter 5 Backtesting
Chapter 6 Trading Strategies
Chapter 7 Factor Investing
Chapter 8 Limit Order
Part III: Portfolio Optimization
Chapter 9 Modern Portfolio Theory
Chapter 10 Convex Optimization
Chapter 11 Risk Parity Portfolios
Part IV: Machine Learning
Chapter 12 Reinforcement Learning
Chapter 13 Deep Learning
Chapter 14 AutoML
Chapter 15 Hierarchical Risk Parity
Part V: Econophysics
Chapter 16 Entropy, Efficiency and Nonlinear Coupling
Chapter 17 Transfer Entropy and Statistical Causality
Chapter 18 Financial Networks
Chapter 19 Fractals and Scaling Laws
Part VI: Alternative Data
Chapter 20 The Market, The Players and The Rules
Chapter 21 Case Studies
The Book is open, so visit our Github project and contribute! The Book is licensed under Attribution-NonCommercial-ShareAlike 4.0 International.