Reading List
Books, papers, and resources that shaped Gordon's design. Ordered by practical relevance.
Essential Books
Robert Carver — "Systematic Trading" (2015)
The most practical book on building systematic trading systems. Covers position sizing, portfolio construction, and the argument for simple strategies. Gordon's volatility targeting and multi-strategy portfolio approach directly follows Carver's framework.
Key takeaway: Simple rules, applied consistently with proper position sizing, beat complex models.
Andreas Clenow — "Following the Trend" (2013)
Demystifies trend-following for managed futures. Shows real portfolio results over decades. The case for trend-following as a legitimate, boring, long-term strategy.
Key takeaway: Trend following works because it's psychologically hard — most people can't sit through the drawdowns.
Marcos Lopez de Prado — "Advances in Financial Machine Learning" (2018)
The reference for applying ML to finance correctly. Triple barrier labeling, meta-labeling, combinatorial purged cross-validation (CPCV), and fractional differentiation. Gordon's v1 research used these techniques extensively.
Key takeaway: Most ML backtests are overfit. Proper validation requires purging overlapping samples and testing on truly out-of-sample data.
Ernest Chan — "Quantitative Trading" (2008)
Practical introduction to quantitative trading for individual traders. Covers backtesting pitfalls, capital allocation, and realistic expectations.
Key takeaway: The edge is smaller than you think, and transaction costs eat more than you expect.
Key Academic Papers
Trend-Following and Momentum
Zarattini et al. (2025) — "Trend-Following with Donchian Channels." The academic basis for Gordon's Donchian ensemble. Shows Sharpe of 1.58 on diversified crypto portfolio, though with more assets and adaptive timeframes than Gordon currently uses.
Han et al. (2024) — Confirms time-series momentum (TSMOM) dominates cross-sectional momentum in crypto. Validates Gordon's approach of comparing each asset to its own history.
Fieberg et al. (2025, JFQA) — Further evidence that TSMOM is the dominant momentum factor in crypto markets.
Bui & Nguyen-Van (2026) — Long-only or 70/30 asymmetric allocation outperforms in crypto due to structural long bias.
Market Microstructure
- Easley & O'Hara (2024) — VPIN (Volume-Synchronized Probability of Informed Trading) as a leading indicator for crypto stress events. The basis for Gordon's planned VPIN kill switch.
Volatility and Risk
- "Momentum Has (Not) Its Moments" (2025) — Volatility-managed momentum improves Sharpe in crypto. Validates Gordon's volatility targeting approach.
Frameworks and Concepts
Walk-Forward Analysis
The standard for honest backtesting of time-series strategies. Instead of random train/test splits, walk-forward slides a training window through time and tests on the immediately following period. See the Walk-Forward Testing page for details.
Ablation Testing
Borrowed from ML research: systematically remove components to measure their individual contribution. In Gordon, every overlay must improve Sharpe in ablation before inclusion. No exceptions.
Kelly Criterion
Optimal bet sizing given an edge and probability. Gordon doesn't use full Kelly (too aggressive for finite-sample estimation), but uses fractional Kelly concepts in position sizing.
Online Resources
Blogs and Sites
- QuantStart — Practical guides on backtesting, strategy development, and infrastructure
- Robot Wealth — Research-driven content on systematic trading
- Quantpedia — Database of trading strategies with academic references
Communities
- r/algotrading — Reddit community for algorithmic trading
- QuantConnect forums — Discussions on systematic strategy development
What NOT to Read
Avoid anything that:
- Promises specific returns or "guaranteed" profits
- Sells expensive courses with cherry-picked backtests
- Focuses on technical analysis "patterns" without statistical validation
- Claims to have a secret indicator or proprietary signal