9.27 CVaR Sizing: One Tool, Two Markets
The CVaR-constrained portfolio QP that sizes Polymarket election arbs is the same machine that sizes a futures book. Different loss shapes, one tail metric, one fix for the correlation that spikes in a crisis.
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. 74
- 5 Microstructure Alpha The order-book layer. The same signal is worthless as taker flow and valuable as a maker improvement. 48
- 6 Portfolio Construction & System Death A real signal still loses if the size and correlations are wrong. Sizing is part of the signal. 55
- 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
9.26 Kelly in Prediction Markets vs a Prop Challenge: Same Formula, Opposite Geometry
Kelly's formula is identical in a prediction market and a prop challenge, but one optimizes long-run growth and the other a first-passage race to a target before an absorbing trapdoor. Opposite geometry, opposite sizes.
9.25 The Market Maker's Impossibility: Speed Versus Accuracy, and Why Arbitrage Is Tolerated
Polymarket could kill structural arbitrage but won't: coherent pricing means an NP-hard solve per trade. It chose speed, pays arbitrageurs roughly 20 percent of fees, and the edge regenerates on every trade forever.
9.24 If You've Used a Softmax Layer, You Already Know the Price Formula
Softmax is the Polymarket price formula. Work one trade to the cent, see why the maker's loss is capped, why the liquidity parameter b sets price impact, and why arbitrage distance is measured in KL, not Euclidean.
9.23 Was It Skill, Structure, or Luck? Execution Efficiency and Regret in Four Buckets
A single P&L number hides four systems and a lot of luck. Grade execution with eta, attribute profit by edge source, split regret into detection, computation, execution, and sizing, and you finally know whether it was skill, structure, or luck.
9.22 The Central Allocator and Non-Negotiable Risk Governors: Proposals, Not Orders
Let five agents touch the wallet and they overspend, stack correlated risk, and breach the tail budget. A single allocator funds proposals by one optimization, and hard risk governors override it to keep you solvent.
9.21 Separate Detection from Execution: A Three-Layer, Typed-Agent Architecture
Wire your solver to your order router and one crash takes down both. Separate detection from execution behind a trade-proposal interface, stack three layers on three clocks, and let a fast scanner trigger the slow solver only where it pays.
9.20 Correlation Lies, Tail Dependence Tells the Truth: Student-t Copulas for Election Portfolios
Five state-election arbs feel diversified until a national shock sinks all five at once. Linear correlation hides that; tail dependence exposes it. Use a Student-t copula and size for the 25-to-1 day.
9.19 The Term Structure of Prediction-Market Strategy and Crowding: Why the Fastest Three Bots Take 80 Percent
A structural arb that printed in October can be worthless by February with no change to the math. Regimes, the term structure of strategy, and crowding decide who actually gets paid, and usually it is not you.
5.39 Big Moves in Lead-Lag: Liquidations, Impact, and News
Lead-lag edge lives in the big moves, so quantile-regress on the tail, not the mean. Then label the cause from trade size and the liquidation feed: impact follows clean, liquidations snap back, and scheduled news is a cue to widen quotes, not to trade.
5.38 Lead-Lag Done Right: Predict and Manage, Don't Naively Wait
The naive lead-lag trade enters B after A moves and exits on a timer. That wastes the edge. Use the slope as a forecast of B's move, exit the instant B hits it, and hold to the horizon only as a backstop.
5.36 Reconstructing the Order Book from Incremental Deltas
The exchange never hands you the order book, just a snapshot plus a firehose of deltas. Fold them in order using a hashmap for O(1) edits and a sorted tree for best bid/ask. Miss one sequence number and every feature silently lies.