MARS Overview · What MARS Actually Does
Fourteen stages between a trade and a permission.
Pipeline stages
14
Evidence fields per trade
17+
Weekly EV classifications
3
Internal regime labels
9
Read this first
Stages 1–3
01Control, capture, and trade-level truth.
Before risk deploys, pre-trade control confirms the asset is approved, the session valid, the branch correctly identified, the stop and target inside the plan, volatility supportive of the intended management model, the risk authorized, the cycle holding capacity, open exposure considered, and fees acceptable — preventing avoidable errors before they enter the data system. Execution is recorded through the broker and TradeZella or equivalent, with the Trade Capture Document acting as a memory bridge to the Saturday review. The CP3 Journal then becomes the primary structured evidence source: it records what happened rather than what the trader remembers happening, because inaccurate source data corrupts every downstream calculation.
Stages 4–6
02Aggregation, expectancy, and capital state.
Weekly_Summary converts individual trades into counts, hit probabilities, average R, risk deployed, fees, adherence, branch contribution, profit factor, RAER, and RAPF — where isolated trades begin becoming performance evidence. The Weekly Trading Scorecard and CP3 EV logic then convert branch probabilities into expected value across Normal, Trend Partial, Trend No-Partial, Overflow, and the blends, classifying the week Green, Yellow, or Red. In parallel, current equity is compared with the latest Equity Peak High; the resulting drawdown determines the gate and brake state — the broad capital posture before any tactical evidence is considered.
Stages 7–8
03Cycle evidence becomes a capital decision.
The Cycle Command Console separates closed realized evidence, open active exposure, floating-R context, remaining risk, cycle P&L direction, daily EV status, and the current gate — closing the gap between individual trades and weekly review. The Throttle Control Panel then issues the decision itself: authorized gate row, maximum tier, final selected tier, authorized cycle pool, average per-trade risk, open-exposure adjustment, fresh deployment capacity, and the final operating directive. This is where evidence becomes a capital decision.
Stages 9–11
04Volatility context, execution efficiency, structural health.
The Volatility Intelligence Panel and Volatility Distance Matrix evaluate whether the market's volatility supports the intended management model — asset, timeframe, session, current versus baseline ATR, relative volatility zone, authority timeframe, trail coefficient, stop distance, and trend quality — decisive for the trend branches, where the trail coefficient materially changes EV, variance, giveback, and fat-tail capture. The MAE/MFE Lab diagnoses whether opportunity was converted into realized expectancy: adverse and favorable excursion, capture efficiency, giveback, stop efficiency, and fee R drag — so when CP3 reveals that EV deteriorated, the Lab can reveal why. The SDE then asks whether the system is improving, weakening, stabilizing, or contradicting itself beneath the P&L: positive EV with worsening drawdown, strong profit factor with poor risk efficiency, equity growth with slowing acceleration.
Stages 12–14
05Regime, benchmark, and the research boundary.
The Regime Classification Engine converts monthly gate and brake telemetry — pressure, structural health, volatility, transitions, persistence, compression — into an internal system-state label from Expansion through Balanced, Transitional, Compression, Fragile Recovery, Instability, Degradation, and Drawdown Control to Critical State. It classifies the condition of the trading operation, not the market, and provides posture without overriding gate authority. Live equity, returns, drawdown, gate dwell, tier usage, and throttle efficiency are then compared against the Monte Carlo benchmark to determine whether performance represents favorable alpha, normal variance, execution drag, excessive risk, or structural underperformance. Finally, controlled research: a proposed rule must be defined, tested, stress-tested, compared with baseline, reviewed for variance and drawdown effects, approved, and deliberately promoted — never allowed to influence production merely because it appears attractive.
How MARS uses this
MARS is a closed loop, not a pipeline. Trades produce evidence, evidence produces weekly grades, grades move gate state, gate state feeds the throttle, and the throttle governs what the next execution is allowed to be. No stage is optional and no stage runs on memory or mood - each one reads the outputs of the stage before it.
How it benefits you
Discipline stops depending on willpower. Because every decision point consumes the previous stage's output, skipping a step becomes visible instead of invisible - and the system keeps improving itself, since every completed loop leaves the evidence base one cycle richer than it found it.
The MARS operating loop: execute, capture, score, gate, throttle, deploy - every cycle feeding evidence into the next.
Reference
The fourteen-stage evidence pipeline
| Stage | What happens | Owning surface |
|---|---|---|
| 1. Pre-trade control | Authorization checklist before any risk deploys | Trading Plan checklist |
| 2. Execution & capture | Broker execution; the capture document bridges to review | Trade Capture Document |
| 3. Journal truth | What happened — not what is remembered | CP3 Journal |
| 4. Weekly aggregation | Trades become counts, probabilities, RAER, RAPF | Weekly_Summary |
| 5. Expectancy conversion | Branch probabilities → EV → Green / Yellow / Red | Weekly Trading Scorecard |
| 6. Capital-state classification | Drawdown from Equity Peak High sets the gate | Gate & Brake architecture |
| 7. Cycle evidence | Closed evidence vs. open exposure vs. floating context | Cycle Command Console |
| 8. Throttle authorization | Evidence becomes the capital decision | Throttle Control Panel |
| 9. Volatility intelligence | Does volatility support the management model? | VIP + Distance Matrix |
| 10. Execution efficiency | Capture, giveback, stop efficiency, fee drag | MAE/MFE Lab |
| 11. Structural diagnosis | Improving, weakening, or contradicting itself? | Structural Diagnostic Engine |
| 12. Regime classification | Monthly telemetry → internal system-state label | Regime Classification Engine |
| 13. Monte Carlo comparison | Live path vs. the 50,000-path envelope | MC Lab benchmark |
| 14. Controlled research | Test → approve → promote; never mutate live rules | EV Labs & Certified Validation QA |
Reference
The MARS authority stack. Authority flows down; evidence flows up; nothing lower may override anything above it.
Go deeper
Operator briefs on this territory.
Deep dive — 01
Fourteen stages produce exactly one permission.
Thirteen stages produce evidence. One produces permission. The shape is a funnel, not a queue.
Read the full brief →
Deep dive — 02
A capture error is invisible to every stage after it.
Every stage downstream validates arithmetic. None validates whether the row is true.
Read the full brief →
Deep dive — 03
Reporting needs a record. Adjudicating needs a rule that existed first.
Six questions. A journal can answer the first. The other five need a prior standard.
Read the full brief →
Every module ships in the complete MARS package.
One price. Eleven workbooks, three TradingView indicators, and the full manual library — $497.