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module · playbooks·9 tactical guides·named & sized

Playbooks, not opinions.

Each playbook names the setup, the regime it works in, the triggers that fire it, the kill criteria that take it off the table, and the cohort statistics from our journal. If a rule isn’t here, it’s not a rule yet.

playbook anatomy
name
setup
regime
trigger[]
kill_criteria[]
cohort.n / expectancy / win_rate
$ ls /playbooks
// catalog · 9 playbooks

The full set, grouped by what they do.

Tap any playbook to expand the full anatomy. Filter by category to find what you need.

filter
thesis

When price probes VAL and the rejection prints with delta turning back into the value area, the market is voting to keep the auction balanced. Fade with a stop one tick below the probe.

trigger[]
  • Regime matrix: rotation OR trend·long
  • Price tags or pierces VAL on the active session profile
  • Delta on the probe bar < -800 reversing to > +200 within 2 bars
  • Flow Pro: GO (long) on the bar that closes back above VAL
kill_criteria[]
  • Two consecutive 1m closes below VAL
  • Regime flips to vol·rising on the rejection bar
  • Delta fails to reclaim positive within 3 bars
thesis

After two genuine pokes that get sold, the third break is almost always weak hands. Fade in the direction of the prior session's value, sized small.

trigger[]
  • ORB high tagged ≥ 3 times within the first 60 min
  • Each tag prints with negative delta and lower-high participation
  • Price closes back inside the range on the failure bar
kill_criteria[]
  • Range expands > 1.5× ATR after entry
  • Vol·rising regime persists for > 15 min after entry
  • Volume on the failure bar < 20-bar median
thesis

Compressions in vol·rising regimes resolve violently. The trade isn&rsquo;t the squeeze, it&rsquo;s the first 1m bar that breaks with confirming participation.

trigger[]
  • ACE Squeeze on 5m: armed for ≥ 6 bars
  • Regime: vol·rising (confidence > 0.55)
  • First 1m bar that closes > 2σ outside the squeeze with delta confirming
kill_criteria[]
  • Two failed pokes in either direction (squeeze head-fake)
  • Regime drops to vol·crush before resolution
thesis

Regime transitions are the single most expensive moment to be aggressive. Most of your worst days started inside a 30-minute window after a regime flip. The trade is no trade.

trigger[]
  • Regime matrix changes state (e.g., trend·long → vol·rising)
  • Confidence on the new state ≥ 0.55
kill_criteria[]
  • 30 min elapsed AND new regime confidence ≥ 0.65
  • OR regime reverts to prior state (likely a noise flip)
thesis

Discretionary overrides are where most of your hidden bleed lives. Audit them weekly. If the override cohort has negative expectancy over 90 days, you&rsquo;re paying tuition for the privilege of being right occasionally.

trigger[]
  • Friday close: pull all trades with override = true from the journal
  • Group by (setup × regime); compute expectancy and sample size
  • Compare against the same (setup × regime) cohort with override = false
kill_criteria[]
  • If trailing-90 override expectancy < base expectancy: ban the override category for two weeks
  • Reinstate only with a written rule for when override is allowed
thesis

The drawdown stop isn&rsquo;t a safety net &mdash; it&rsquo;s the single highest-EV rule in your book. Most blowups happen in the last 20% of the loss, not the first 80%. Quit before the math turns vicious.

trigger[]
  • Intraday P&L hits -1.5R (after fees)
  • OR weekly P&L hits -3R cumulative
kill_criteria[]
  • Stop is non-negotiable; reactivate next session
  • If you breach without honoring the stop: 5-day platform timeout
thesis

Most exit systems fail because they&rsquo;re too tight in trend and too wide in chop. The JMA adapts; the time exit prevents you from holding a winner into a regime that no longer supports it.

trigger[]
  • Position is in profit > 1R
  • Trail at the 5m JMA(14) with a 1-tick buffer
  • Hard exit if regime flips out of trend·long/short
kill_criteria[]
  • Regime flip exits immediately, even at a draw
  • Time exit at session close regardless of P&L
thesis

Most strategies fail in production because they were promoted too early. Five hard gates &mdash; if you can&rsquo;t pass them, you don&rsquo;t deploy.

trigger[]
  • Walk-forward DSR > 0.5 across 3 windows
  • PBO (probability of backtest overfitting) < 0.4
  • MAR > 0.8 on out-of-sample
  • Live paper trading: 30 days, > 50 trades, P&L within 1σ of expected
  • Code review by a second person, including risk gate integration
kill_criteria[]
  • Failure of any gate: back to research
  • If two strategies in a row fail gate 4: rebuild research methodology
thesis

The day after a -3R is statistically the worst day in your book. Tilt drives over-sizing; over-sizing drives the second loss. The protocol is a forced cooling-off plus a structured re-entry.

trigger[]
  • Daily P&L closes ≤ -3R
  • Or weekly P&L hits the -5R cumulative line
kill_criteria[]
  • 24-hour platform lock (auto)
  • Re-entry only after a journal review of the trades that caused the loss
  • Position size capped at 0.5x for the next 5 trades
playbooks · 9 · curated·cohort-backed·updated weekly

Read the playbook. Then run it inside the platform.

Each playbook is a self-contained tactical guide. Inside the Swing Desk, the same triggers and kill criteria are wired directly into the scoring layer — you don’t have to remember the rule, the rule reminds you.