Jul 12
Every Custom Indicator and Tool I've Built for StrategyQuant
Most traders who use StrategyQuant treat it as a finished product: open the box, generate strategies, done. I have spent the better part of a decade treating it as a platform to build on. When the tool I needed did not exist — an indicator, a robustness test, a way to score a databank — I coded it myself. And most of the time, I published it back to the community.
As of today that comes to 135 separate extensions in the StrategyQuant Codebase: 81 custom indicators and signals, 29 databank and analytics columns, 5 Monte Carlo robustness tests, and a set of What-If and workflow tools. Every one of them is free, downloadable, and in use by traders around the world.
This page is a map of that toolkit — organised not alphabetically, but by what each piece is for. If you build systematic strategies, you will recognise most of the problems these were written to solve.
Everything here runs inside StrategyQuant X, the platform I build in. In the interest of full disclosure: the StrategyQuant links on this page are affiliate links — if you start there through them I may earn a commission, at no extra cost to you. The Codebase blocks themselves are, and always will be, free to download and use.
Custom indicators and signals
The largest part of the collection — 81 indicators and signal blocks. Some are faithful implementations of classics that were simply missing from the platform; many are adaptive or statistical tools you will not find anywhere else. Here is how they break down.
Smart Money Concepts
The vocabulary of institutional order flow, turned into blocks you can actually generate strategies with. I have written elsewhere about treating Smart Money Concepts as geometry rather than mysticism — these are the tools that make that possible: Order Block Detector, Break of Structure, Fair Value Gap, Simple Liquidity Sweep and the Swing Failure Index.
Adaptive and dynamic averages
A moving average with a fixed period is always fighting the last regime. These adjust their responsiveness to volatility or efficiency in real time: VIDYA, the Variable Moving Average, HalfTrend, the Volatility Skew Tracker and band variants like HalfTrend Bollinger Bands. If you want the reasoning behind them, I covered why adaptive indicators beat fixed-period ones in a dedicated post.
Statistical and market-regime tools
This is where my data-science background shows. Instead of asking “is price above the average?”, these ask “has the distribution of returns changed?” — the difference between a strategy that notices a regime shift and one that trades straight through it. The set includes the Kolmogorov–Smirnov Test, Wasserstein Distance, Dynamic Time Warping, CUSUM and the Hurst Exponent. There is a full write-up on statistical regime detection if this is your area.
Volatility and risk
Position sizing and exits live or die on a good volatility estimate. These give you several: ATR Trailing Stops, Smoothed ATR With Bands, the TTM Squeeze and the Waddah Attar Explosion. The trailing-stop block in particular has its own guide.
Momentum and oscillators
Twenty-odd momentum tools, from well-known names implemented properly to a few you may not have met: WaveTrend, Schaff Trend Cycle, RCI3Lines, the David Varadi Oscillator and the Relative Vigor Index, among many others.
Advanced and DSP filters
For when you want to treat price as a signal-processing problem: a Kalman Filter, Ehlers’ Mother of All Moving Averages and Hilbert Transform, and the composite MAMA/FAMA/KAMA block.
VWAP and moving-average families
Rounding out the set: VWAP and its band variants, Hull Moving Average Bollinger Bands, and Kaufman’s Efficiency Ratio.
This is a selection — you can browse all 81 indicators in the Codebase.
Databank and analytics columns
Building strategies is only half the job. The harder half is deciding which of the thousands you have generated are actually worth keeping — and that is a measurement problem. These 29 custom columns are the anti-overfitting arsenal I use to rank and filter a databank on metrics the platform does not ship with.
A few I reach for constantly: Timothy Masters’ Internal Profit Factor, which measures profit quality per bar rather than per trade (I explained why it is so revealing here); the Trade Edge Ratio, a favour-versus-adversity measure that predicts out-of-sample survival better than most; a full set of Walk Forward Optimisation Metrics; and a Multimarket Analysis column that scores how a strategy holds up across instruments it was never fitted to — the single best overfitting check I know.
Monte Carlo robustness tests
A backtest is one lucky path through history. These five tests generate hundreds of plausible alternative histories and ask whether the edge survives all of them — the difference between a genuinely robust strategy and one that only looks good on paper. They are the exact tests I walk through in my guide to Monte Carlo robustness testing: MACHR Block Randomization, Parameter Jitter, Degrade Execution, and swap-sensitivity tests at both the individual-trade and whole-backtest level.
What-If and workflow tools
The rest of the collection is quieter but saves real time: What-If scenario tools that let you ask questions like when your system should actually be allowed to trade, long-only and short-only simulations, money-management overlays, and custom-analysis snippets that rename, rank and select strategies in bulk.
The ones I did not publish
Everything above is public. A large share of my actual client work is not — bespoke blocks built for a specific edge, a specific instrument, or a specific prop-firm rule set. The 135 published pieces are, in a sense, the reusable core; the interesting work is usually the custom block that does not generalise enough to share.
If there is an indicator, filter or robustness test you wish StrategyQuant had — or you want an existing idea coded cleanly as a reusable block — that is exactly the kind of thing I do. You will need StrategyQuant X to run any of it, and everything in the Codebase is free to start with.
If you want a specific edge built, tested for robustness, and handed over as a clean block you can actually trade, that is what I do.