6.54 Volatility Clustering in Bitcoin: Regime Persistence as a Forecast
Bitcoin vol clustering: a 3-state Markov chain shows persistence above 0.9 -- High state delivers ~9% moves in 48h, but thresholds are look-ahead by construction.
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. 41
- 4 Market Structure Notes The same rule is edge on one instrument and noise on another. Read a market's personality before you deploy. 76
- 5 Microstructure Alpha The order-book layer. The same signal is worthless as taker flow and valuable as a maker improvement. 51
- 6 Portfolio Construction & System Death A real signal still loses if the size and correlations are wrong. Sizing is part of the signal. 56
- 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. 10
- 9 Prediction Market Arbitrage The cleanest money on Polymarket and Kalshi comes from prices that contradict each other, not prices that turn out wrong. 41
- 10 Cross-Sectional & Factor Investing Stop timing one asset. Rank the whole cross-section and let relative value, not direction, carry the return. 19
Latest articles
4.75 Stock-Bond Correlation: The Sign Flips and So Do Its Drivers
Stock-bond correlation flipped from +0.22 to -0.24 around 2000 across G7 markets. Real rates most stable driver. US portfolios need 80% stocks post-2000 to match 50/50 pre-2000 performance.
5.50 Market Making With Competitors You Can't See
Add a competitor's inventory as a second state variable in Avellaneda-Stoikov: a matrix ODE closed form beats PPO (500M epochs, 99% paired-t). The fill you miss shifts their next quote and degrades yours.
5.49 The Worst-Kept Secret: Imbalance Is the MM's Optimal Response, Not Alpha
Order book imbalance predicts price moves because a market maker who knows the true price posts it that way to manage her own inventory risk, not because it leaks information.
5.51 Crypto Isn't Structurally Alien: Roll/VPIN/Amihud Predict Distribution Shifts
Crypto VPIN of 0.47 sounds toxic until you derive the estimator's null value: 0.500. And the Roll measure that drives every prediction is mostly a volatility proxy. One label of five survives.
4.74 FX Edge Lives in Other Markets (cross-asset series)
FX edge sits in the graph: EM stocks lead by a month, G10 loops pay daily, and FX futures Sharpe jumps from 0.16 to 0.66 once other asset classes are wired in.
9.43 There Is No Black-Scholes for Prediction Markets (Yet)
A belief-vol kernel needs prices that sum to $1 and carry no predictable drift. Polymarket prices sum to $0.60, $39.6M walked out, and a $2 shove still moves a market 60 days later.
3.39 Does Complexity Actually Help? The Virtue-of-Complexity Autopsy
KMZ's virtue of complexity survives only under a zero-intercept restriction and a per-draw scoring rule. Fix either and it reverses: 15 predictors beat 12,000, and buy-and-hold beats both.
3.41 Metaheuristics for Rule Optimization — With Diversity as the Guardrail
Four optimizers, 31 seeds, one BTC rule set. The useful output is not which one won, it is that Differential Evolution's population stayed 82% scattered after 1000 generations.
1.28 Model-Based or Data-Mined: Lotter's Framing of the Whole Problem
Lotter splits strategy building into model-based and data-mined, then shows a random walk you cannot tell from EUR/USD. His own reality-check slide has a p-value near 0.085.
10.14 Price-Path Convexity: A New Cross-Sectional Anomaly (−45bp per σ)
Two stocks end the month flat, one by recovering, one by fading. The shape between the endpoints predicts next month: low-convexity stocks beat high-convexity by 0.84%/mo, and no factor explains it.
10.12 Factor Timing Mostly Fails — the Honest Version
Value, momentum, volatility, and sentiment timing all lost to a plain equal-weight factor basket in China. Theory says timing is huge; estimation error eats it. Trust the plateau, not the peak.