Table of Contents
This interview features Omar—an OG voice on trading Twitter and YouTube—sitting down in New York for the Words of Wisdom podcast. He’s the founder of Train and Trade and a straight-talker about how he went from equity markets to forex, why 24/5 charts nearly broke his sleep cycle, and how working nights in a shisha lounge funded those early $500–$2,000 deposits. You’ll hear how a handful of mentors shaped his playbook, why he stuck with EURUSD as a mainstay, and why crypto lives on his higher timeframes. He matters because he’s actually shipped results, talked through real losses, and still shows up with practical rules instead of hype.
You’ll learn the strategy levers that moved Omar from small personal accounts to reliable prop-firm payouts: selecting one or two instruments, anchoring entries to H1/H4 on BTC, and protecting psychology by matching risk models to prop rules. He unpacks passing challenges without worshiping them, why personal accounts still matter, and how to handle slow weeks without forcing trades. Expect takeaways on discipline, journaling one setup until it sticks, muting social media noise, and building a brand that funds the craft—so the trading stays calm, focused, and scalable.
Omar Agag Playbook & Strategy: How He Actually Trades
Core Framework: Markets, Sessions, and Focus
Here’s the big picture of how Omar keeps his trading simple and repeatable. You’ll pick one or two instruments, anchor to specific sessions, and avoid the “trade everything” trap that kills consistency.
- Pick 1–2 core markets and specialize (e.g., EURUSD and BTC).
- Define your active windows: Asia 9–10 pm, London 3–4 am, New York 8–9 am, London closes 11 am–12 pm (NY time).
- If you miss your window, you missed the trade—do not “make it up” later.
- Pre-mark weekly and daily key levels on Sunday; refine before each session.
- Turn off all non-core pairs and symbols during your session to prevent FOMO.
Top-Down Workflow: From Bias to Execution
Omar builds a directional bias on higher timeframes and only then drills down for precise entries. This keeps trades aligned with structure instead of random scalps.
- Start weekly/daily: mark highs/lows, fair value gaps, imbalances, and obvious liquidity pools.
- Set session bias on H4/H1 (premium/discount relative to the last impulse).
- Drop to M15/M5 only after HTF bias is set; if bias is unclear, skip the session.
- Trade toward fresh liquidity (equal highs/lows, prior day’s extreme, session high/low).
- No counter-bias trades unless the HTF is invalidated via a close beyond your level.
Entry Triggers: Liquidity + Displacement (ICT-Style, Simplified)
Omar’s entries are built around clean liquidity events and strong displacement. Here’s the distilled rule set so you don’t overcomplicate it.
- Wait for a liquidity sweep of a clear level (equal highs/lows, Asia range, previous session extreme).
- Require displacement: a long, impulsive candle that breaks structure, not a grind.
- Enter on a return to the fair value gap or last up/down candle before the break (mitigation).
- Invalidation = last swing beyond your mitigation zone; stop goes just beyond that.
- If price hesitates at mid-range and fails to displace, pass and re-assess—no forced fills.
Risk Sizing & Trade Management: Keep It Mechanical
The edge is at risk, not predictions. Omar’s sizing and partials are rules-based, so psychology doesn’t hijack the session.
- Risk 0.25%–0.5% per idea on personal accounts; 0.15%–0.3% on prop accounts.
- First partial at 1R, second partial at 2R; move stop to break-even after first partial.
- Hold a runner only if the HTF target/imbalance is still in play; otherwise, flatten at 2–3R.
- Never widen stops after entry; if invalidated, exit and log it.
- Max 2 trades per session, 1 losing streak allowance (stop after 2 red trades).
Prop-Firm Playbook: Pass and Keep Payouts Flowing
Prop rules are different from personal accounts. Omar adapts to drawdown limits and payout cycles without changing the core method.
- Risk small and steady: target 0.5%–1.5% per day, not home runs.
- Set a weekly hard stop at 2% total drawdown; pause trading if hit.
- Avoid trading near news that can spike slippage against the max daily loss.
- Bank early partials (1R) to reduce equity volatility and protect the evaluation phase.
- If you’re ahead of target mid-week, cut the size in half and focus on A+ only.
BTC & High-Beta Swing Variant: Fewer Trades, Bigger Moves
For BTC and similar movers, Omar shifts to higher timeframes and lets imbalances do the heavy lifting. This is the slower lane with cleaner targets.
- Build bias on D1/H4; execute on H1/M15 only if displacement is decisive.
- Use wider stops sized to the same risk %, not to the same pip count.
- Partial at prior daily swing; trail behind H1 structure until invalidated.
- Avoid weekend chop; evaluate Sunday evening, trade Monday–Friday only.
- One setup per day max—skip if the candle bodies are overlapping and wicky.
Playbook for Slow Weeks: Maintain Edge Without Forcing
Some weeks won’t give you clean sweeps or displacement. Omar stays selective and preserves mental capital.
- Trade only if your session gives a sweep + displacement; otherwise, journal and stand down.
- Run a micro-risk “observation” position (≤0.1%) only to collect data—no expectations.
- Tighten your watchlist to one market; close the chart after the window ends.
- Increase reading/backtesting time; tag 10 historical examples of your A+ setup.
- No revenge sessions outside your scheduled windows.
Daily Routine & Journal: Make It Repeatable
Omar’s routine is boring on purpose—because boring is consistent. You’ll capture the same screenshots and notes every day.
- Pre-session (15 minutes): HTF levels update, bias statement, “If-Then” plan in one sentence.
- Post-trade: screenshot entry, exit, and HTF context; tag with setup name and R multiple.
- End-of-day: log emotions (1–10), adherence score (%, not vibes), and one improvement.
- Weekly: export win rate, average R, and rule-adherence; set next week’s max trades.
- Delete indicators you didn’t use this week; de-clutter charts to core tools.
Psychology & Noise Control: Protect Attention
The method works only if your head is clear. Omar limits inputs so execution stays sharp during the session.
- Mute social feeds and signals during your windows; reopen after journaling is done.
- Pre-commit to two scenarios (trend/mean-revert) and ignore all others that appear mid-session.
- Use a timer: 45–90 minutes on, then step away; don’t babysit noise.
- If you break a rule, reduce the size by half for the next three trades.
- Sleep and hydration are part of the plan—no late-night scalp after a short night.
Branding & Business Hygiene (Optional but Smart)
Trading funds the brand, and the brand can smooth income variability. Omar keeps it practical and aligned with the craft.
- Share only finalized lessons and marked-up charts; no live “guessing” content.
- Batch content outside trading hours; never let posting disrupt sessions.
- Keep payouts and personal account growth as North Stars; views are a bonus.
- Track time spent on brand work; cap it if performance dips.
- Document your playbook publicly only after 100 logged trades of the setup.
Set Risk Per Trade and Stop After Two Losses
Omar Agag keeps it simple: choose a fixed risk percent per idea and defend it like a rule, not a suggestion. For most traders, that means 0.25%–0.5% per trade, so one mistake can’t ruin the week. He sizes the stop from the structure first, then adjusts the lot size to match the risk, never the other way around. If the setup can’t fit inside that predefined risk, Omar Agag passes and waits for a cleaner context.
The second piece is the session brake: stop trading after two consecutive losses—full stop. This prevents tilt, protects evaluation accounts, and keeps the day’s loss inside a recoverable range. He reviews the two losers, screenshots them, and only returns next session with a fresh plan. With a hard cap on damage and a fixed-percentage risk, Omar Agag turns variance into something he can survive—and then exploit—over the next hundred trades.
Let Volatility Decide Position Size, Not Your Emotions
Omar Agag sizes trades to market movement, not mood swings. He starts with a structure for the stop, then uses recent volatility to scale the position so the same risk percent survives both quiet and fast markets. If ATR or session range expands, the position shrinks; if it compresses, size can step up—risk percent stays constant. This keeps drawdowns steadier and prevents the “same stop, random size” mistake that wrecks prop evaluations.
When volatility spikes into news or a breakout day, Omar Agag trims size automatically and aims for cleaner displacement before pulling the trigger. On sleepy ranges, he accepts smaller targets but maintains discipline on entries and partials. The rule is simple: adapt size to the tape you’re trading today, not the confidence you feel. Volatility-led sizing makes each trade just another sample in a long, survivable series.
Build One Playbook Setup and Trade It Across Sessions
Omar Agag’s edge comes from repetition, not variety. He picks one clean setup—liquidity sweep, displacement, and a return-to-entry zone—and hunts it the same way in London and New York. By drilling the same pattern, he knows the failure tells, the average R multiple, and the best partial points. The chart gets simpler, execution gets faster, and the journal fills with comparable data instead of random screenshots.
Across sessions, Omar Agag keeps the rules identical and only changes the clock. If a session prints the setup, he takes it; if it doesn’t, he stands down without improvising a new system on the fly. After 50–100 trades of that one setup, he can tune it with real stats rather than gut feel. Mastering one repeatable pattern turns trading from guessing into a process—and turns each session into just another chance to execute the same play.
Diversify By Instrument, Strategy, and Holding Duration
Omar Agag treats diversification as risk control, not a scavenger hunt for more trades. He spreads exposure across a couple of uncorrelated instruments, mixes one core setup with a slower swing variant, and staggers holding times so not everything wins or loses together. That way, a choppy EURUSD morning doesn’t sink the week if a BTC H4 swing is still trending. He caps overlap—no doubling up on two pairs that move off the same USD impulse.
Omar Agag also diversifies by time-in-market to smooth equity curves. A quick session trade might bank 1–2R, while a higher-timeframe position hunts a clean imbalance toward a daily target. He tracks each “bucket” separately—intraday, swing, and optional event-avoidance plays—so sizing, targets, and expectations stay clear and disciplined.
Trade Mechanics Over Predictions: Liquidity, Displacement, Then Targets
Omar Agag puts mechanics first and prediction last. Start by mapping resting liquidity—equal highs/lows, Asia range, prior session extremes—and wait for a clean sweep. Demand a decisive displacement candle that breaks structure; grinding price action doesn’t qualify. Only then look to enter on the return to the fair value gap or the last opposing candle (mitigation).
Invalidation is the prior swing beyond your mitigation zone; if tagged, close and reset. Targets are mechanical too: session high/low, previous day’s extremes, or obvious inefficiency fills. Take partials at 1R and 2R, then trail behind the structure only while displacement remains intact. If the sweep or displacement never shows, skip the trade mechanics over guesses, every time.
Omar Agag’s interview boils down to a practical blueprint: simplify, specialize, and protect your downside. He keeps a tight universe of instruments, builds a directional bias on higher timeframes, and only executes when the tape shows a clean liquidity event and decisive follow-through. The stop is placed from structure first, the position size is set by volatility, and the risk percent per idea never changes. When the market is messy or the setup doesn’t trigger, he skips the trade—because survival and selectivity beat constant action.
He treats prop accounts like a different sport: smaller per-trade risk, early partials, and strict daily/weekly loss caps to keep evaluations and payouts intact. For high-beta names like BTC, he zooms out, accepts fewer entries, and aims for imbalance fills on the higher timeframes. Journaling is non-negotiable—screenshots, R-multiples, and rule adherence—so the playbook evolves from data, not feelings. Above all, Omar Agag frames trading as mechanics over prediction: find the liquidity, demand displacement, manage risk with discipline, and let the next hundred trades—not one hero call—write your equity curve.
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