77 lines
3.7 KiB
Markdown
77 lines
3.7 KiB
Markdown
# Roadmap
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My roadmap for becoming competent quant and capable of creating automated trading bots.
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Current Goal: **Learn Quantitative Foundations**
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## Study
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Current reading [Introduction to Probability, Statistics, and Random Processes - Hossein Pishro-Nik](./textbooks/reading/20260622012450_Introduction%20to%20Probability,%20Statistics,%20and%20Random%20Processes/Introduction%20to%20Probability,%20Statistics,%20and%20Random%20Processes%20-%20Hossein%20Pishro-Nik.pdf) and [Algorithmic Trading](./textbooks/reading/20260622012451_Algorithmic%20Trading%20Winning%20Strategies%20and%20their%20rationale/Algorithmic%20Trading%20Winning%20Strategies%20and%20their%20rationale.pdf)
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## Phases
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Recommended path, generated by CLAUDE
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### Phase 1 — Math Foundation (*)
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1. [ ] Pishro-Nik (*)
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2. [x] Quantitative Trading
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3. [ ] Elementary Stochastic Calculus
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4. [ ] A guide to Brownian motion
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### Phase 2 — Get Practical Early
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1. [ ] Algorithmic Trading — Chan ← read this soon; short, orients everything else
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2. [ ] Analysis of Financial Time Series — Tsay ← essential for price/return modeling
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### Phase 3 — Core Quant ML
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1. [ ] Data-Driven Science and Engineering — Brunton & Kutz
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2. [ ] Advances in Financial Machine Learning — Lopez de Prado ← most important book in your backlog
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3. [ ] Stochastic Calculus: An Introduction with Applications ← now the theory lands better
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4. [ ] Detecting Regime Change in Computational Finance
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### Phase 4 — Portfolio, Risk & Systems
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1. [ ] Active Portfolio Management — Grinold & Kahn
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2. [ ] The Microstructure of Financial Markets — de Jong & Rindi
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3. [ ] Trading Systems and Methods — Kaufman (use as reference)
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4. [ ] The Mathematics of Money Management — Vince
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5. [ ] The Leverage Space Trading Model — Vince
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6. [ ]Testing and Tuning Market Trading Systems
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### Phase 5 — Specialized / Optional
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1. [ ] Assessing and Improving Prediction and Classification (C++ heavy, niche)
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2. [ ] Trading on Sentiment (alt data / NLP, very specialized)
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3. [ ] Numerical Recipes (reference only, don't read cover to cover)
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4. [ ] Measure Theory (only if you want pure math depth — lowest ROI for bots)
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### Missing textbooks
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- Systematic Trading: A unique new method for designing trading and investing systems
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- Permutation and Randomization Tests for Trading System Development: Algorithms in C++
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## Textbooks
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- *Introduction to Probability, Statistics, and Random Processes* - Hossein Pishro-Nik
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- *Quantitative Trading* - Ernest P. Chan
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- *Algorithmic Trading: Winning Strategies and Their Rationale* - Ernest P. Chan
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- *Elementary Stochastic Calculus* - Thomas Mikosch
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- *A Guide to Brownian Motion and Related Stochastic Processes* - Jim Pitman & Marc Yor
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- *Stochastic Calculus: An Introduction with Applications* - Bernt Øksendal
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- *Active Portfolio Management* - Richard Grinold & Ronald Kahn
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- *Probability and Statistics: The Science of Uncertainty* - Michael J. Evans & Jeffrey S. Rosenthal
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- *Analysis of Financial Time Series* - Ruey S. Tsay
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- *Data-Driven Science and Engineering* - Steven L. Brunton & J. Nathan Kutz
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- *Advances in Financial Machine Learning* - Marcos Lopez de Prado
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- *Detecting Regime Change in Computational Finance* - Timothy Masters
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- *Trading Systems and Methods* - Perry J. Kaufman
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- *The Mathematics of Money Management* - Ralph Vince
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- *The Leverage Space Trading Model* - Ralph Vince
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- *Testing and Tuning Market Trading Systems* - Timothy Masters
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- *Assessing and Improving Prediction and Classification* - Timothy Masters
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- *Trading on Sentiment* - Richard L. Peterson
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- *Numerical Recipes: The Art of Scientific Computing* - Press, Teukolsky, Vetterling & Flannery
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- *An Introduction to Measure Theory* - Terence Tao
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