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.
The return you predict matters more than the 147 features you feed the model. Demeaning, standardizing, or ranking the target moves monthly alpha ~0.9pp; feature transforms move it ~0.4pp.
Landolfi's percentile-rank momentum: rank moves against their own sign-consistent past, gate them with a hysteresis band to kill churn, validate with a walk-forward bundle. Steal the plumbing, doubt the crypto curve.
Polymarket prices do converge to the truth over 90 days. But they are far more volatile than stocks or crypto, overprice longshots (slope 1.13 > 1), and lean "yes." The edge: bet favorites, early.
Decentralized prediction markets, cut into eight swappable stages. Seven are engineering trade-offs. The eighth, resolution, is where a handful of token wallets can settle a market against the truth.
CryptoMamba, a compact Mamba SSM, forecasts Bitcoin's next close and trades $100 into $262. But it never runs the naive or buy-and-hold baselines, on one bull year of daily bars.
A 14B model trained with outcome-only RL matched o1 and beat it on calibration. The lesson: drop GRPO's variance scaling, block leakage, and the win is honest probabilities, not beating the market.
When the game is against you, betting small is slow suicide. Bold play, swinging your whole stack at the target, maximizes your chance of hitting it. Optimal bet size flips with the sign of your edge.
Hyperliquid runs fully on-chain, so a node captures every order event: wallet IDs, counterparty inventory, and the ~89% of orders that are rejected and invisible in LOBSTER-style data.
Two economists shocked 817 prediction markets by 5 points each. Sixty days later the shove was still there. Prices revert, but slowly, partly, and cheaply beaten in thin markets.
A prediction-market price is not a probability. It is where capital-weighted Kelly bets cancel. You bet the gap, not the belief, and getting the probability wrong costs more than mis-sizing.
Prediction markets have no Black-Scholes. A recent paper builds one: model log-odds as a jump-diffusion, force the price to be a martingale, trade what's left. Clean theory, thin evidence.
A two-regime MS-GARCH turned 7% buy-and-hold lumber into 158%. The edge was all in the asymmetric variance model. Adding market and behavioral factors made the good versions worse.