5.53 Where Is Bitcoin's Price Actually Set? Unregulated Venues Win
Bitcoin price discovery squares the ratio of the Hasbrouck share to the component share, in a 10-millisecond error-correction model. The cheapest book takes the permanent move.
Independent research on systematic & quantitative trading
Aligrithm is an independent research publication on systematic trading, quantitative research, market microstructure, and adaptive systems. Long-form essays, code notebooks, and architecture breakdowns across eight pillars, built for traders who care more about how markets behave than about hype.
More about the publication →The ten pillars
Read in order. Each pillar walks you out of one trap with one new ability. The newest article is the worst place to begin.
- 1 The Scientific Trader Rebuild what you accept as evidence. Every rule becomes a hypothesis, every backtest an experiment you can falsify. 28
- 2 Indicator Engineering The input decides the ceiling. Build features with measurable properties that survive the tests. 82
- 3 Robust Systems Lab A strategy is not robust for surviving one friendly backtest. Here it survives hostile testing. 46
- 4 Market Structure Notes The same rule is edge on one instrument and noise on another. Read a market's personality before you deploy. 77
- 5 Microstructure Alpha The order-book layer. The same signal is worthless as taker flow and valuable as a maker improvement. 55
- 6 Portfolio Construction & System Death A real signal still loses if the size and correlations are wrong. Sizing is part of the signal. 59
- 7 Python Research Notebooks Stop taking results on faith. Re-run every claim on your own data and see whether it holds. 5
- 8 Physics, Geometry & Event-Driven Markets The frontier. Markets as event-driven nonlinear systems, not fixed-time price series. Read it last. 12
- 9 Prediction Market Arbitrage The cleanest money on Polymarket and Kalshi comes from prices that contradict each other, not prices that turn out wrong. 42
- 10 Cross-Sectional & Factor Investing Stop timing one asset. Rank the whole cross-section and let relative value, not direction, carry the return. 25
Latest articles
10.20 A Trend Factor for the Crypto Cross-Section (and Its Overfit Tell)
Crypto trend factor CTREND earns 3.87% a week, Sharpe 1.94. On 55,296 designs the median Sharpe is 1.34, and 1.94 sits at the top of the grid.
10.19 Crypto Has Fundamentals: A Seven-Factor Model (Read Skeptically)
Crypto factor model Q-7: on-chain quality posts a t-stat of 9.80 and a 245% annual long-short. The authors' survivor universe leaves that spread in the table.
3.47 The Real IS→OOS Sharpe Haircut (Closed Form, Not "50%")
Sharpe ratio haircut: a 10-year commodity momentum fit keeps about 30% out of sample. The flat 50% rule is one cell, and often the wrong one.
5.51 Better Inputs Beat Deeper Nets: Crypto LOB Direction
Crypto LOB direction: a logistic regression matches DeepLOB at 0.73 accuracy on one Bybit day. The Kalman filter drops the same call below a coin flip.
10.24 Learning to Rank, the Original: Pairwise and Listwise Cross-Sectional Momentum
Cross-sectional momentum keeps the order and throws the forecast level away. A pairwise loss trains which name outranks which. Squared error can tie and still swap the book.
3.40 Does Complexity Actually Help? (flagship)
Out-of-sample Sharpe: 12,000 features score 0.49 and lose to buy-and-hold at 0.55. Complexity pays only with more data, by 0.12%/month on a global cross-section.
3.49 Building a Statistically Valid Backtest: The Checklist Nobody Runs
Backtest overfitting: stock predictors fall 26% out of sample and 58% after publication, and the median Sharpe of 215 smart-beta strategies falls 73% once live.
6.62 Polynomial Regression Bands With a Profit Factor Below One
Nasdaq-100 polynomial regression bands: the four-degree model is crowned on a 0.55 profit factor. That 0.55 is one losing stock, and average profit factor falls from 1.76 to 1.60.
5.56 Spot-Futures Manipulation in Crypto: Pump Spot, Trap Perp Longs, Dump
Crypto microstructure: Binance alt spikes flagged as spot-futures manipulation lag other spikes by 0.83% in 2 hours and 1.64% in 24 hours. The flag is a heuristic.
10.21 Is Attention a Factor? WSB Herding, BERT Sentiment, and the Meme Confound
WallStreetBets attention factor: FF4 alpha 112.58% a year, 64.22% after GME and AMC. The three-name 20-day drift is -0.05%, t on the single name is 0.51.
10.16 ML in the Cross Section: Avramov's Companion to the DDA3600 Spine
Neural-net cross-section alpha dies once you drop microcaps and charge 0.50% of turnover: FF6 0.31% vs cost 0.43%. Linear IPCA still clears, 0.61% vs 0.57%.