NAKAMOTO Trading AcademyNAKAMOTO visual academyLibrary home

Evidence-based strategy systems

Trading Strategy Lab

A professional lab for turning trading concepts into testable, repeatable, risk-defined systems. Education only: no trade signals, no profit guarantees, no gambling frameworks.

All strategies below are research templates. A setup is not valid until it has written rules, backtest evidence, forward-test evidence, execution constraints, risk limits, and review data.

Trading lab architecture

Concepts become systems only after validation.

Every model moves through the same pipeline: hypothesis, market condition, rules, risk, test, review, refine, and only then playbook inclusion.

StageRequired OutputFailure FilterEvidence NeededStatus
1. HypothesisOne-sentence edge premiseVague pattern namingMarket condition and reasonRequired
2. RulesEntry, stop, exit, invalidationDiscretion without documentationChecklist and examplesRequired
3. RiskRisk per trade, max daily loss, drawdown stopOversizing after lossesRisk model and journal logRequired
4. ValidationBacktest and forward testCherry-picked examplesSample size, expectancy, varianceRequired
5. ReviewPerformance review and error taxonomyNo post-trade feedbackMonthly reportRequired

Strategy library

Professional playbooks with rules, risk, and validation requirements.

Each strategy is a template for research and practice. The lab separates context, setup, trigger, risk, management, and review.

Market Structure Reversal

Setup: trend loses continuation, sweeps an extreme, then prints CHoCH/BOS against prior trend. Risk profile: higher false-break risk, requires strict invalidation.

  • Entry rules: failed continuation, liquidity sweep, structure shift, retest of break area.
  • Stop rules: beyond swept extreme or invalidation block.
  • Common mistake: calling every pullback a reversal.
  • Validation: compare first reversal attempt vs second attempt after failed continuation.

Supply And Demand Retest

Setup: strong departure from a zone, return to origin, confirmation reaction. Confirmation: rejection, absorption, structure shift, or failed attempt through zone.

  • Entry rules: zone must have imbalance departure and untested area.
  • Stop rules: outside zone plus volatility buffer.
  • Exit rules: opposing zone, liquidity objective, or failure to leave zone.
  • Disadvantage: zones become weak after repeated tests.

Price Action Pullback

Setup: trend or breakout environment followed by controlled pullback. Trigger: rejection candle, engulfing confirmation, or break-and-retest continuation.

  • Entry rules: context first, candle second. Candle signal cannot stand alone.
  • Stop rules: beyond pullback low/high or trigger invalidation.
  • Common mistake: trading pin bars without trend or level context.
  • Validation: categorize by pullback depth, location, and preceding impulse.

Auction Rejection Model

Setup: price tests value extreme or prior balance edge and fails to accept. Context: balance, range, failed breakout, or prior value area.

  • Entry rules: test outside value, rejection back inside, confirmation rotation.
  • Stop rules: beyond rejection extreme.
  • Exit rules: mid-value, POC, opposite value edge.
  • Validation: test VAH/VAL rejection separately from LVN rejection.

Auction Acceptance Model

Setup: price moves beyond value and holds there. Condition: acceptance through time, volume, or repeated failure to return into prior value.

  • Entry rules: acceptance above VAH or below VAL, retest holds, continuation structure.
  • Stop rules: back inside rejected value area.
  • Exit rules: next HVN/LVN, measured range extension, or new balance.
  • Common mistake: treating a single wick as acceptance.

Volume Profile Value Migration

Setup: POC/value shifts in direction of active participation. Use: bias and trade location, not standalone entry.

  • Entry rules: align structure with value migration and responsive pullback.
  • Stop rules: failed acceptance or migration reversal.
  • Exit rules: next value node, LVN rejection, or balance formation.
  • Validation: separate trend days, range days, and news volatility days.

Order Flow Absorption

Setup: aggressive buying or selling fails to move price through a key area. Confirmation: footprint imbalance absorbed, delta divergence, failed continuation.

  • Entry rules: key level plus visible absorption plus structure trigger.
  • Stop rules: beyond absorbed area after failure threshold.
  • Risk: requires high-quality data and platform familiarity.
  • Validation: tag absorption at highs, lows, and inside ranges separately.

Liquidity Sweep Reversal

Setup: price sweeps obvious liquidity, fails to continue, and reclaims the prior range. Concepts: stops, inducement, failed breakout, rejection.

  • Entry rules: sweep, reclaim, displacement or structure shift, retest.
  • Stop rules: beyond sweep extreme.
  • Exit rules: opposing liquidity or value target.
  • Common mistake: shorting/longing every sweep without confirmation.

ICT / SMC FVG Continuation

Setup: displacement creates fair value gap after structure shift and liquidity context. Condition: trade from premium/discount alignment, not isolated FVG.

  • Entry rules: liquidity event, BOS/CHoCH, displacement, FVG retracement, continuation trigger.
  • Stop rules: beyond invalidation swing or order block.
  • Exit rules: liquidity objective or opposing imbalance.
  • Validation: classify by session, HTF bias, and FVG depth.

Elliott Wave Context Framework

Use: context and bias framework, not isolated signal. Condition: identify impulse/corrective structure with invalidation points.

  • Entry rules: only after separate price-action or structure trigger.
  • Stop rules: wave invalidation level.
  • Disadvantage: subjective counts and hindsight bias.
  • Validation: require alternate count and invalidation before trade idea.

Quant Research Framework

Setup: transform a discretionary idea into variables. Example variables: trend state, value location, volatility, session, trigger, stop distance, target distance.

  • Backtest: define sample, market, dates, inclusion rules, fees, slippage.
  • Metrics: win rate, average win/loss, expectancy, max drawdown, profit factor, variance.
  • Forward test: paper/live simulation before capital risk.
  • Failure filter: reject strategies that only work after cherry-picking.

Risk and psychology systems

Capital preservation is the operating system.

A strategy without risk controls is not a professional system.

SystemRulesReview MetricFailure ModeControl
Position SizingFixed fractional risk, max risk per trade, contract multiplier checkRisk varianceOversizing after confidencePre-trade calculator
Drawdown ControlDaily loss stop, weekly loss stop, pause after rule breaksPeak-to-trough drawdownRevenge tradingLockout rule
Trade ManagementPredefined partials, invalidation, target, trail ruleMAE/MFERandom exitsManagement checklist
PsychologyPre-market state check, post-trade emotion tag, weekly reviewRule adherenceImpulse executionJournal and review

Journal Template

  1. Date/session
  2. Strategy model
  3. Market condition
  4. Entry trigger
  5. Invalidation
  6. Risk amount
  7. Emotion state
  8. Rule adherence
  9. Lesson learned

Performance Review Template

  1. Number of trades
  2. Win rate and expectancy
  3. Average win/loss
  4. Max drawdown
  5. Best/worst setup type
  6. Top rule break
  7. Next improvement action

Beginner-to-professional roadmap

Strategy maturity is earned through evidence.

The lab moves learners from pattern awareness to process governance.

2

Intermediate

Build written setup rules, practice examples, and learn failure cases.

Practice
3

Advanced

Backtest, forward test, classify market conditions, and measure expectancy.

Validate
4

Professional

Run playbooks, portfolio risk, process reviews, research updates, and governance.

Operate

Strategy lab FAQ

How to use this lab correctly.

These answers keep the lab focused on validation, not signal chasing.

Is a playbook a trade signal?

No. A playbook is a research template. It still needs market context, rules, testing, risk limits, and review.

When is a strategy ready?

Only after the setup, entry, stop, exit, risk model, sample size, and review process are written and tested.

Can beginners use this?

Yes, but beginners should start with structure, risk, glossary terms, and chart drills before advanced playbooks.

What should I track?

Track market condition, rule adherence, R result, mistake tag, emotional state, and screenshot evidence.