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.
A large order moves price by construction, so it manufactures the move it seemed to predict. Size needs capital and a firm view, which reads like information on the tape, so the market prices large flow as informed because it cannot tell you apart. Read the permanent impact to separate knowing from
The seller is easy to picture, so everyone narrates the seller after a crash. Price is set at the margin: the question that forecasts anything is who the marginal buyer is, and where they step back.
Got forecasts on different clocks? Don't pick the biggest. Normalize each to edge-per-second on its markout curve (30 bps/60s = 0.5 vs 2 bps/1s = 2) and average the curves to blend fast and slow edge into one.
Volatility predicts the size of a move, not its direction, so it can't trade alone. Multiply it by momentum and it works, until extreme vol gains its own sign, down for equities and up for gold.
The Fourier transform fails on price but nails a robot, because a wash bot or metronomic TWAP is the clean periodic signal price never is. Bin trades, FFT the counts, and a sharp spike is automation. The catch: your own equal-interval TWAP makes that spike, so randomize it.
The cheapest way for an MFT shop to enter a small position is to act like a market maker: feed your quoting engine a phantom short so it skews and fills you long, collecting the spread instead of paying it.
Three fair-value estimators for an adjacent crude future, each too weak alone: spread EMA, returns beta, cross-book volume. Weight each by one over its error variance and the shared signal survives while the noise cancels.
The clean linear factor model fails because its weights are not constants. Momentum and carry only pay in the right vol regime, and interactions are the one thing a linear model cannot represent.
Bar research assumes the clock drives the market. It doesn't, events do. Fixed rebalance times are front-runnable and bars hide execution seasonality. Screen on bars, validate on event-driven sims, trade on events.
Every moving average is a low-pass filter, and its lag is the price of stripping noise from a causal signal. Read indicators as filter weights, not chart lines, and stop fooling yourself about them.
Commodities are priced in dollars, so a weaker dollar makes them cheaper abroad, lifts foreign demand, and raises their price, which lifts the commodity currencies. Use it as a directional gate, and count the dollar once.
A cross has no dollar to lean on, so trade it off the relative performance of the two countries' stock indices. Divide them in logs, signal off the ratio, and confirm the equities actually lead the cross.