Roadmap

My roadmap for becoming competent quant and capable of creating automated trading bots.

Current Goal: Learn Quantitative Foundations

Study

Current reading Introduction to Probability, Statistics, and Random Processes - Hossein Pishro-Nik and Algorithmic Trading

Phases

Recommended path, generated by CLAUDE

Phase 1 — Math Foundation (*)

1. Pishro-Nik (*)
2. Quantitative Trading
3. Elementary Stochastic Calculus
4. A guide to Brownian motion

Phase 2 — Get Practical Early

1. Algorithmic Trading — Chan ← read this soon; short, orients everything else
2. Analysis of Financial Time Series — Tsay ← essential for price/return modeling

Phase 3 — Core Quant ML

1. Data-Driven Science and Engineering — Brunton & Kutz
2. Advances in Financial Machine Learning — Lopez de Prado ← most important book in your backlog
3. Stochastic Calculus: An Introduction with Applications ← now the theory lands better
4. Detecting Regime Change in Computational Finance

Phase 4 — Portfolio, Risk & Systems

1. Active Portfolio Management — Grinold & Kahn
2. The Microstructure of Financial Markets — de Jong & Rindi
3. Trading Systems and Methods — Kaufman (use as reference)
4. The Mathematics of Money Management — Vince
5. The Leverage Space Trading Model — Vince
6. Testing and Tuning Market Trading Systems

Phase 5 — Specialized / Optional

1. Assessing and Improving Prediction and Classification (C++ heavy, niche)
2. Trading on Sentiment (alt data / NLP, very specialized)
3. Numerical Recipes (reference only, don't read cover to cover)
4. Measure Theory (only if you want pure math depth — lowest ROI for bots)

Missing textbooks

• Systematic Trading: A unique new method for designing trading and investing systems
• Permutation and Randomization Tests for Trading System Development: Algorithms in C++

Textbooks

• Introduction to Probability, Statistics, and Random Processes - Hossein Pishro-Nik
• Quantitative Trading - Ernest P. Chan
• Algorithmic Trading: Winning Strategies and Their Rationale - Ernest P. Chan
• Elementary Stochastic Calculus - Thomas Mikosch
• A Guide to Brownian Motion and Related Stochastic Processes - Jim Pitman & Marc Yor
• Stochastic Calculus: An Introduction with Applications - Bernt Øksendal
• Active Portfolio Management - Richard Grinold & Ronald Kahn
• Probability and Statistics: The Science of Uncertainty - Michael J. Evans & Jeffrey S. Rosenthal
• Analysis of Financial Time Series - Ruey S. Tsay
• Data-Driven Science and Engineering - Steven L. Brunton & J. Nathan Kutz
• Advances in Financial Machine Learning - Marcos Lopez de Prado
• Detecting Regime Change in Computational Finance - Timothy Masters
• Trading Systems and Methods - Perry J. Kaufman
• The Mathematics of Money Management - Ralph Vince
• The Leverage Space Trading Model - Ralph Vince
• Testing and Tuning Market Trading Systems - Timothy Masters
• Assessing and Improving Prediction and Classification - Timothy Masters
• Trading on Sentiment - Richard L. Peterson
• Numerical Recipes: The Art of Scientific Computing - Press, Teukolsky, Vetterling & Flannery
• An Introduction to Measure Theory - Terence Tao