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 →Read in order. Each pillar walks you out of one trap with one new ability. The newest article is the worst place to begin.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Market impact is the cost you simulate, not look up: walk the book level by level, slippage = (avg - mid)/mid x 1e4, then fit a·x^b. The exponent near 0.5 is the square-root law, and it lets you price sizes past the visible book.
A big maker's PnL isn't the spread, it's positional: skewing thousands of weak alphas into passive quotes. Zero cost makes half-bp signals tradeable, and ensembling them cancels noise into the bulk of the profit.