Price Action Naked Trading Playbook

Introduction

A playbook is not a collection of pretty pictures of setups. It is an operational document: when you trade, on which market, with which model, for how much, when you stop and how you measure whether it works. Without a playbook you have a collection of concepts. With a playbook you have a repeatable process.

This final lesson merges the previous 6 into a single system that you can test, implement and improve. We will build a Price Action playbook template, journaling rules, evaluation metrics and a 30-day implementation plan. This is the most important lesson in the course.

The architecture of a Price Action playbook

The playbook consists of 7 sections:

1. Universe and timeframes
2. Structural definitions (objective)
3. Context filters (when I trade, when I do not)
4. Entry models (setups with criteria)
5. Risk and position management
6. Journal and metrics
7. Review and optimisation plan

Every section must be written so that another person could reproduce your decisions without guessing.

1. Universe and timeframes

Why limit the markets? Because every market has a different volatility, ATR and behaviour at a sweep. 1-3 markets let you build intuition and statistics.

2. Structural definitions

You have to write down:

Swing High/Low: N=2 (M15), N=3 (H4)
BOS: body close beyond the major swing + a 0.15 ATR H4 buffer
CHOCH: break of the last defended HL/LH
Demand/Supply: impulse >1.5 ATR, base 1-4 candles, fresh
FVG: min 0.4 ATR H4, unfilled
Order Block: the last opposite candle before an impulse >1.5 ATR + BOS
Liquidity: EQH/EQL difference <0.15 ATR, PDH/PDL, Weekly High/Low
Sweep: 0.3-0.7 ATR beyond the level, return <3 H1 candles

Without that, your tests are unmeasurable.

3. Context filters

When you look for a setup and when you do not.

I trade when:

• HTF trend defined (not a range <0.8 ATR wide for 20 candles)
• Price in an HTF Demand/Supply zone or at HTF BSL/SSL liquidity
• No high-impact news within 30 minutes
• Block Quality Score >=2 (from lesson 5)

I do not trade when:

• HTF consolidation without a BOS for >2 days
• Sweep >1.2 ATR without a return
• Zone used up (2+ tests)
• Emotional tilt (3 losses in a row, see the section below)

4. Entry models – specification

Choose 1 main and 1 additional from lesson 6. Describe it like an algorithm.

Example: Main model – BOS Retry in HTF Demand

CONTEXT:
HTF = H4 uptrend (HH/HL, the last HL defended)
Zone = Fresh H4 Demand, Q >=3

LTF EXECUTION = M15:
1. Price enters H4 Demand (touches 50% of the zone)
2. Wait for a bullish CHOCH on M15 (break of the last M15 LH)
3. Wait for a bullish BOS on M15
4. ENTRY: Market after the M15 BOS or Limit on a retest of the BOS level
5. STOP: Behind the M15 HL that formed after the CHOCH + 0.2 ATR M15
6. INVALIDATION: M15 close below the HL or H4 close below Demand
7. TP1: 1.5R (close 50% or move to BE)
8. TP2: The next H4 BSL (Weekly High/PDH/EQH) or a fixed 2.5R
9. BE: After reaching 1R or after an M15 BOS in your direction

Every model must have a “code” like this.

5. Risk management

Risk per trade: 0.75% of capital
Max daily loss: 2% -> end of day
Max weekly loss: 5% -> break until Monday
Max 3 losses in a row -> 24h break
Target R-multiple: 2R
Minimum risk/reward to enter: 1.5R

Position calculation:
Position = (Capital * Risk%) / (Entry - SL in currency)

Rules:
- I do not move the SL further away (beyond BE per plan)
- I do not add to a losing position without a new LTF setup
- I do not increase the % after a winning streak (anti-martingale)

6. Journal and metrics

A Price Action journal must contain an HTF and LTF screenshot before and after, plus measurable data.

Journal table:

Weekly metrics to calculate:
Win Rate = Wins / All
Avg Win R = average R of the wins
Avg Loss R = average R of the losses (should be ~ -1R)
EV per trade = (WR * AvgWinR) - ((1-WR)*AvgLossR)
Profit Factor = Sum of winning R / Sum of |R| of the losses
Max DD in R = the largest equity drop in R units
Frequency = how many setups per week
Adherence = % of trades consistent with the playbook (target >90%)

Formulas:
EV = (WinRate * AvgWin) - (LossRate * AvgLoss)
PF = Sum(Wins R) / Sum(|Losses R|)
Expectancy = EV * number of trades per day * days

Goal at the start: Adherence >90%. Not profit. If adherence is high and EV is negative, you improve the model. If adherence is low, you do not know whether the model works, because you are not executing it.

7. Review plan

Three ready-made mini-playbook templates (choose one)

A. Trend Continuation (for beginners, the simplest)

• HTF up/downtrend clear
• Only BOS Retry in a fresh HTF Demand/Supply
• No trading around news, London+NY only
• TP a fixed 2R, BE after 1R
• Structural LTF stop

B. Liquidity Reversal (intermediate, better R:R)

• HTF range or extreme + EQH/EQL + BSL/SSL
• Sweep Reversal model after the return + an LTF CHOCH/BOS
• Stop beyond the sweep + 0.2 ATR
• TP to the opposite HTF liquidity

C. Breakout + Breaker (active, more trades)

• HTF consolidation with EQH/EQL
• Breakout + HTF BOS
• Wait for a return to the Breaker Block
• LTF CHOCH/BOS entry in the Breaker
• Stop behind the Breaker

Every template must be tested on 30 demo trades or a backtest before you move to live with a micro position.

When the plan says do not trade – playbook rules

1. When adherence <80% in the last week: Stop. You go back to demo for 1 week. There is no point measuring EV if you are not executing the plan.
2. When the max daily/weekly loss is reached: The end. You close the platform. This is not a suggestion, it is a system rule. Every breach of this rule destroys your statistics.
3. When you have an open position and you cannot manage it according to the BE/TP plan: Do not open new ones. 1 position max is the anti-tilt rule.
4. When the Quality Score is <2 and you are “stretching” a setup out of boredom: Boredom is part of the playbook. 70% of days are observation. If there is no Q>=2 setup, there is no trade.
5. When you are after a strong emotion (a big win/loss, an argument, no sleep): Price Action requires clarity. Only play in the “objective observer” state. Otherwise it is a day OFF.

The mistakes that cost the most

1. No written definitions. “A swing high is a peak you can see”. That is not a definition. A backtest of such a definition is impossible. Every definition must have N, ATR and a buffer.
2. Optimising after 5 trades. Changing the TP from 2R to 3R because 2 trades paid more. That is randomness. Change every 30 trades minimum, and only one variable at a time.
3. Mixing models in one playbook. Sometimes BOS Retry, sometimes Sweep, sometimes Breaker with no Q Score. The result: you do not know what works. Choose 1 main one.
4. No journal with R-multiples. You remember only the big wins. The losses “disappear”. Without a journal in R there is no growth.
5. Scaling the risk % before 100 trades with positive EV. You increase the lot because 10 trades in a row were profitable. Then 3 losses wipe out a week. Scale risk only when you have 100 trades and a stable PF >1.2 and EV >0.1R.

Measurable exercise – a 30-day implementation

Week 1 – Definitions and Backtest:

• Write down the definitions (section 2).
• Backtest 30 setups on H4/M15 historically. Record Q, the model, the 2R result with no emotion. Calculate EV.

Week 2 – Demo Forward:

• 5 days of live demo, max 2 trades a day, according to model A/B/C. Count adherence.

Week 3 – Micro Live or still Demo:

• 0.5% risk. 5 days. The goal is adherence >90%, not profit.

Week 4 – Review:

• Calculate: WR, AvgWinR, AvgLossR, EV, PF, MaxDD, Adherence.
• Answer: Do I continue this model? What do I change (1 thing)?

Price Action course completion criteria:
- 30 trades in the journal with HTF/LTF screenshots
- Adherence >85%
- EV calculated and written down
- 1 thing to improve over the next 30 trades defined

Only after that can you think about increasing risk or adding a second market.

Check yourself

1. List the 7 sections of a Price Action playbook.
2. You have 40 trades: 18 wins averaging 2.1R, 22 losses averaging -1R. Calculate EV and Profit Factor.
3. Why is adherence more important than Win Rate at the start?
4. Describe your main entry model in 5 steps like an algorithm.
5. When should you stop trading for the day/week according to the playbook?

Frequently asked questions

Does the playbook have to be 10 pages long? No. It should be 1-2 A4 pages, operational. Definitions, filters, the entry model with conditions, risk, journal. The simpler it is, the higher the adherence. A complicated playbook with 5 models will never be executed.

Can I trade 2 models at once? You can have 1 main and 1 additional, but measure them separately. If you have 2 main ones from the start, you do not know which one delivers EV. Start with 1.

How often should I change the playbook? Every 30 trades, review the small parameters (buffer, BE timing). Every 100 trades, a strategic review (whether the model makes sense). Not every day. Frequent changes are overfitting and a lack of data.

What if my market stops working (EV falls below 0)? That is normal – the market regime changes. That is why you have consolidation, session and Q Score filters. If after 30 trades in a trending regime EV is still negative despite adherence >90%, the model needs modification or a change of market. That is a signal, not a failure.

Do I have to trade every day? No. Your playbook can assume 2-3 trading days a week in the best windows. What matters is that the window is written down and that outside it you do not trade impulsively. Boredom is part of the plan.

Can I add an indicator, e.g. an EMA 200, as an HTF filter? Yes, but only after 100 trades of pure Price Action. First you have to know whether pure structure has EV. Only then do you measure whether adding an EMA filter increases EV or merely reduces the number of trades without improving PF. A filter without measurement is noise.

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