2.72 The Volume-Weighted MA Ratio
The volume-weighted MA ratio asks where the crowd transacted, not which way it pushed: VWMA over SMA, above one when expensive bars carried the volume. Log it, scale by root-lookback, compress, and it's model-ready.
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. 70
- 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. 47
- 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. 8
- 9 Prediction Market Arbitrage The cleanest money on Polymarket and Kalshi comes from prices that contradict each other, not prices that turn out wrong. 33
- 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
2.49 The Decycler Oscillator: Spotting Trend Transitions
Subtract a long-cutoff high-pass from a short-cutoff one and you get the decycler oscillator, a band-pass whose zero crossings flag trend transitions. Use it to classify the regime, not as a trigger.
2.71 Normalized On-Balance Volume
OBV's running sum wanders like a random walk and depends on when you started counting. Window it, divide signed volume by total volume, scale by root-lookback, and you get a bounded, stationary flow oscillator.
2.48 The Weighted Moving Average Was a Mistake
The WMA ramps weights toward recent bars, so its coefficients are asymmetric, breaking linear phase and warping shape. It lags more than the SMA at equal noise rejection; a real window beats both.
2.70 Intraday Intensity and Chaikin Money Flow, Made Stationary
Raw Intraday Intensity whipsaws and drifts upward for years as volume grows, useless. Divide summed money flow by summed volume and you get Chaikin Money Flow: bounded, stationary, model-ready.
2.47 Critical Period and the Half-Power Point: How to Pick Filter Length
A filter's critical period is its half-power point: amplitude 0.707, not 0.5. For an SMA it's twice the length, so SMA(50) targets a 100-bar cycle. Pick length on purpose; the lag comes attached.
2.69 Reactivity: Momentum Times Aspect Ratio
Reactivity weights momentum by an aspect ratio, range per unit of volume, so a big move on thin volume scores high. Powerful for trading cycles, but it multiplies two noisy parts, so normalize both halves or it lies.
2.46 The SMA Is a Least-Squares Straight-Line Fit
The SMA is the optimal least-squares fit of a flat line to the window: the intercept is the average. But that assumes the market is constant plus noise, so it lags trends and erases matched cycles.
2.68 The Price Change Oscillator
Short-term movement minus a long-term baseline, normalized by ATR, reads volatility expansion against contraction. But normalize too hard and you delete the very regime signal you wanted: the stationarity-vs-information trade-off, with a dial.
2.45 Nyquist and Aliasing: The Hard Limit on What Price Data Can Show
Sample once per bar and the fastest cycle you can see is 2 bars (Nyquist). Anything faster aliases: it folds down and masquerades as a slow cycle that was never there, and no filter can unmask it.
2.67 Deviation from Expectation: Trend Projection as a Signal
Fit a trend, project it one bar forward, and subtract it from the actual close. A small gap means the trend holds; a big one means it just broke. A regime-break kill switch, built on log prices and ATR, not raw price.
2.44 The Filter Coefficient Cookbook: One Equation for EMA, LPF, HPF, BPF
EMA, low-pass, high-pass, band-pass, band-stop are one second-order equation with different coefficients, built from the period via alpha. One engine and a recipe table, not a drawer of indicators.