6.10 How to Build a Cost-Aware RSI Ranking System
RSI as a 70/30 trigger is noise. Z-score it cross-sectionally, check the shape, rank and risk-size the extremes, then buffer the turnover. The four-step pipeline works for any indicator.
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. 26
- 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. 37
- 4 Market Structure Notes The same rule is edge on one instrument and noise on another. Read a market's personality before you deploy. 71
- 5 Microstructure Alpha The order-book layer. The same signal is worthless as taker flow and valuable as a maker improvement. 45
- 6 Portfolio Construction & System Death A real signal still loses if the size and correlations are wrong. Sizing is part of the signal. 48
- 7 Python Research Notebooks Stop taking results on faith. Re-run every claim on your own data and see whether it holds. 3
- 8 Physics, Geometry & Event-Driven Markets The frontier. Markets as event-driven nonlinear systems, not fixed-time price series. Read it last. 9
- 9 Prediction Market Arbitrage The cleanest money on Polymarket and Kalshi comes from prices that contradict each other, not prices that turn out wrong. 34
- 10 Cross-Sectional & Factor Investing Stop timing one asset. Rank the whole cross-section and let relative value, not direction, carry the return. 15
Latest articles
6.1 Ranking Beats Forecasting for Many Trading Problems
For cross-sectional strategies you don't need to predict returns, only to order them. Ranking throws away the fragile magnitude and keeps the part that survives regime shifts.
5.21 Cross-Exchange Fair Value for Crypto Perps
On a follower crypto venue, your local mid is stale. Build fair value from the leader: regress the basis against Binance's mid, blend global and local prices, and respect the stablecoin rates.
5.20 Dynamic Symbol Selection for Market Makers
A maker shouldn't quote everything. Track the EWMA markout of every trade in a symbol, quote only the non-toxic names, and scale size by markout. Selection alone can turn a flat system profitable.
5.19 Maker vs Taker Edge: Same Signal, Different Economics
One signal, two businesses. The taker pays the spread and needs a strong edge; the maker earns it and thrives on weak ones across a wider universe at higher frequency. The spread divides them.
5.18 Why Small Alphas Matter More for Makers Than Takers
A half-bp signal is garbage to a taker who pays the spread and money to a maker who collects it. That cost flip turns thousands of weak alphas into the bulk of a maker's PnL.
5.17 TWAP and VWAP Are Execution Models, Not Just Indicators
TWAP and VWAP are not indicators to cross over. They are execution benchmarks and the slicing algorithms built to hit them, the machinery for moving a large order without blowing out the price.
5.16 Fill Probability from Trade Size CDFs
A quote's PnL is easy; its fill probability is the hard part. Build a CDF of taker order sizes and read off the chance the next trade is big enough to clear the queue ahead of you plus your own size.
5.15 Using Trade Flow to Predict Short-Term Price Movement
Trade flow reads liquidity being taken, not posted. Signed and summed, it predicts price because trades are autocorrelated: buys follow buys. And unlike book imbalance, executions can't be spoofed.
5.14 Microprice: Better Than Mid Price?
The plain mid ignores resting sizes. The weighted mid and microprice lean the center toward the thin side, where price is headed, giving a maker a fair value that already respects the book.
5.13 Order Book Imbalance: The First Microstructure Feature to Test
Order book imbalance, bid size minus ask size over their sum, is the strongest simple microstructure feature. Price rolls toward the thin side, and the signal lives in the tails, so fit a spline.
5.12 Spoofing, Sturdy Liquidity, and Book Pressure
Half the big orders in crypto are spoofs that vanish on approach. Lean on one and the price runs through your fill. Filter for sturdy size, and trade the turn a spoof's disappearance creates.