Simplest Lab is a private market research practice built around one operating principle — that the best place to operate from in any complex system is the simplest possible version of the truth. Every tool, every framework, every signal in the lab exists because a simpler version of a complex problem was found.
Markets are complex adaptive systems. The instinct is to meet that complexity with complexity — more indicators, more data, more conditions. The lab was built on the opposite instinct.
Most trading systems fail not because they lack information, but because they carry too much of it. Every additional variable introduces a new failure mode. Every new indicator adds latency between signal and action. The more complex the system, the more places it can break — and the harder it becomes to know which part broke.
The market doesn't reward the most sophisticated model. It rewards the most consistently executed edge. And consistency requires simplicity.
The foundational insight behind the lab's primary tool is that price velocity — how fast a stock is moving relative to its own historical average — is one of the purest signals available. It doesn't require predicting direction. It simply measures whether something is moving unusually fast, and in what structural context.
From that single measurement, everything else follows: trend alignment, setup classification, relative performance ranking. The V% ratio was designed to be the minimum sufficient statistic for identifying high-probability momentum setups.
No single signal trades in isolation. The macro dashboards — SPY Confluence Matrix, Bitcoin Matrix — exist because individual signals are noisy. What they measure in aggregate is something more durable: the degree to which multiple independent systems agree about the current market regime.
When velocity, structure, sentiment, and macro all point the same direction, the setup is actionable. When they diverge, patience is the position.
The name is not a starting point — it's a destination. Every methodology begins complex. It earns its simplicity through iteration, through failure, through the slow process of removing everything that doesn't carry signal. What remains is the simplest version that still works. That's the version worth operating from.
The starting point. Remove what you know is noise. Establish what you know is signal. Build from first principles, not inherited complexity. A simple system that works is infinitely more valuable than a complex one that almost works.
The process. Pressure test every component. If removing it doesn't hurt performance, remove it. Refinement is the discipline of subtraction — the willingness to let go of complexity that feels meaningful but adds no edge.
The destination. The form a good system takes when it has nothing left to remove. Obvious in retrospect, invisible in execution. This is where consistency lives — where the gap between knowing and doing closes to zero.
Each instrument in the lab is built around a single core measurement, layered with structural context, and filtered by confluence. The formulas are transparent. The logic is documented. Nothing is a black box.
The foundational metric. Measures how aggressively a stock moved this week relative to its own 14-period average weekly range. Normalized to the weekly open so the anchor is where the week began, not where it ended.
Every V% qualified stock is classified by its MA structure and price position. REV (reversal), PBK (pullback), and EXT (extended) labels identify the structural setup. Parenthetical versions denote the bearish mirror of each setup.
The macro dashboards score 10 independent metrics across 5 analytical layers — technical structure, breadth, sentiment, macro, and geopolitical risk. Each metric is weighted. The composite score defines the market regime for the week.
Dominant trend is defined by agreement across all four performance timeframes — 1 month, 3 months, 6 months, and 1 year. All positive = uptrend. All negative = downtrend. Any disagreement = mixed. No exceptions.