Video Summary - STEAL The 1-Minute Strategy That Made Him $1.8M+ (Works Every Session)

Finance-focused summary (Prop-firm futures trading)

Core strategy: “Fair price” mechanical price-action approach (NQ / NASDAQ futures)

JJ Simon describes a mechanical price-action method built around a concept of “fair price” derived from:

Session opens (especially the 9:30 a.m. EST market open)
News events (expected vs. unexpected outcomes)

Timeframe discipline

Entries are taken only on the 1-minute timeframe.

Trading objective

Exploit an “unfair” displacement away from fair value, then capture:
- Reversion trades back to the fair price (primary edge)
- Continuation trades in some cases (often lower expected value than reversion)

“Fair price” definitions used

Market open (9:30 a.m. EST)

Fair price is initially set to the 9:30 open price.
Later adjustments occur based on:
- what happens after the open
- unexpected news moves
Fair price becomes the post-news consolidation when relevant.

News days

Expected red-folder news (8:30 a.m. EST; e.g., CPI/PPI)
- Fair price is typically anchored to the pre-news price
- Rationale: the move is “priced in,” so large deviations tend to revert.
Unexpected news (e.g., tweets/speeches)
- Fair price is updated to the most recent consolidation after the shock.

Step-by-step framework / rules (as stated)

Time window

Trades are limited to the first 90 minutes of each session, explicitly including:

New York
Asia
New York PM

Setup types

1) Continuation trade (once per session)

Enter in the direction of the opening candle, if it aligns with the high-timeframe reversion bias.
Bias is described as “inverting” prior 6–12 hours.
Entry logic (1-minute)
- First candle color
- “Breaks structure”
Fixed example risk/targets
- TP: 38 points
- SL: 25 points
If the opening candle is > 25 points, he cuts contract size in half to keep dollar risk consistent.

2) Reversion trades toward fair price (primary)

Entry signals on the 1-minute chart only:

Displacement candle
- Candle body is larger than the prior candle’s body
- Closes below the prior candle wick (for shorts; analogous logic for longs implied)
- Used to take reversion entries toward fair value.
Break of structure
- Wick makes a new low (or a structural break) versus prior candles
- The next candle breaks structure
- Considered a stronger entry signal (especially for funded accounts).

Prop-firm-optimized targets
- TP is selected to match prop rules (e.g., 25/50/100 points depending on the account).
- When it breaks structure, he marks expected return points to fair value and chooses the account whose TP best fits.

Execution discipline

Uses candle closes for confirmation:
- “Always waiting for candle closes on displacement and breakup structures.”

Risk management

Uses static risk and static take profits for prop-firm EV modeling.
Stop-loss is described as “optimized,” but often treated as effectively static / reciprocal to TP dollar amount (focus is placed on TP first).

EV / risk-to-reward logic and quantitative claims

Statistically optimal risk/reward (for prop firms)

JJ claims there is a statistically optimal risk/reward depending on:

account drawdown rules (how much drawdown is available)
rules like consistency
win rate

Example

If trading 1:4 risk-to-reward, his required win rate is about 20%:
- “Then my bias only needs to be right about 20% of the time.”

Key emphasis

Prop firms reward static R/R modeling more than “live-equity backtests.”

Consistency accounts (different rule set)

For consistency rules (example: 50% consistency rule):

He reduces aggressiveness:
- typically 1:1.5 R:R
- sometimes 1:2, depending on profit targets
He warns against aiming for 1:4 on consistency accounts because:
- with the win-rate requirement implied by 1:4, consistency rules can effectively demand too many R-multiples.

Evaluation vs funded targets

Evaluations
- Often have fixed profit targets and max losses with profiles resembling ~1:1.0 to 1:1.5
- He tends to use displacement entries to increase trade frequency.
Funded accounts
- He prefers break of structure entries for higher-quality triggers.
- He chooses account types where the fair-value distance matches the account’s optimized TP (e.g., 100-point trades if available).

News trading framework and examples

Expected news (8:30 a.m. EST “red folder”)

Expected releases (e.g., CPI, PPI) are described as forecasted and mostly priced in:
- “90% of the time it’s very very close to the forecast.”
After the expected-news shock:
- initial move is unfair
- he trades reversion using the same displacement / structure entry model
Target is reversion toward the pre-news price.

Unexpected news (tweets/speeches/Fed chair)

Unexpected items can change fair price, not just create an entry opportunity for reversion.

Post-shock plan

Update fair value to the latest consolidation
Trade either:
- continuation (news drift), or
- reversion back to the new consolidation fair price

Prop-firm scaling system (multi-account management)

Multi-account execution

He manages multiple simultaneous accounts:
- aiming for ~40+ accounts, later saying ~45 accounts
Uses software workflow:
- “I use Trade of 8” (tab/workflow for trade management)
- Opens multiple “tabs” and layers entries across accounts

Layering and exposure control

He avoids duplicating exposure in the same account.
He can swap between:
- funded accounts
- evaluation trades to manage variance.

Stop after losses

“If I lose three in a row, then I’m done” (per session).
He suggests the reversion bias is invalidated when the market trends (not reverting).

Backtesting / validation methodology (step-by-step)

Backtest like prop firms, not like equity trading

JJ admonishes against backtesting as if it were normal live equity performance.

How to backtest for prop-firm success

Backtest in a prop-firm environment:
- simulate 10 funded accounts
- apply the same static risk/reward on every account/trade
- evaluate pass rate (not smooth equity curve)
For evaluation pass-rate:
- simulate ~50 evaluations to reduce variance

Funding cost model

He provides a funding acquisition cost equation:

cost of a funded account = (evaluation cost) / (pass rate)

Example

If pass rate = 25%, then $100 eval implies $400 long-run to obtain a funded account.

Profitability condition

Expected value of the funded account must exceed acquisition cost.

Live-account EV considerations

He claims expected value for a live account roughly equals starting capital if break-even.
- Example: if $10,000 live account, EV ≈ $10,000 (minus fees)
EV must be recalculated if firms move you to live due to:
- SIM profit conversion
- live balance caps / bonuses
- reduced SIM risk capacity

Risk cautions and limitations emphasized

Variance risk
- Trading variance is significant; sample size matters.
- Recommends 50 evals for a better pass-rate estimate.
Rules changing / live-account enforcement
- EV may increase or decrease depending on:
  - how often firms move traders live
  - whether live changes drawdown/payout rules
Trailing drawdown / EV degradation
- Taking profit can reduce remaining drawdown capacity in trailing regimes, harming EV.
Bias might fail
- Fair price is adjusted when trades lose (discretionary fair-value adaptation).
- Stops after 3 consecutive losses in a session.

Key numbers and performance metrics mentioned

Starting capital: ~$5,000
Early monthly payout growth (as stated):
- Month 1: $17,000
- Month 2: around $20k, then $40k, $60k, $80k, $100k
Total payout claim:
- $1.8M+ (over $1.5M payouts referenced)
Example trade targets:
- TP 38 points, SL 25 points (first continuation example)
- Funded TP ranges referenced: 25 / 50 / 75 / 100 points
Consistency example:
- 20% win-rate requirement in the 1:4 example
Evaluation example details:
- mentions $2,000 max loss and $3,000 profit target, implying roughly 1:1.5

Instruments / assets explicitly mentioned

NASDAQ futures
NQ futures
Red folder news at 8:30 a.m. EST
CPI, PPI
Forex Factory (calendar source)
No specific public equity tickers/ETFs are named.

Disclosures / disclaimers

No explicit “not financial advice” disclaimer appears in the provided subtitles.
The content is framed as a trading/prop-firm strategy explanation and includes promotional segments for trading/education tools.

Presenters / sources mentioned

JJ Simon (main presenter)
Chart Academy (education platform; sponsor/mentioned)
Apex Trader Funding (prop firm; sponsor/mentioned)
NinjaTrader (trading platform; sponsor/mentioned)
TradeZella (AI trading platform; sponsor/mentioned)
Riz (host/interviewer referenced near the end)

STEAL The 1-Minute Strategy That Made Him $1.8M+ (Works Every Session)

Key takeaways