Table of Contents
This episode features Omor, a 21-year-old trader steeped in ICT/SMC concepts, sitting down in Dubai for a straight-talk conversation about how he actually trades and why time matters more than most people think. He walks through, blowing an early account, regrouping, and then getting funded—a context that makes his framework resonate for anyone trying to move from theory to consistent execution. Omor isn’t selling vibes; he’s stitching together market structure with higher-time-frame narrative, kill zones, and a realistic approach to risk—exactly the blend most retail traders miss.
Read on to learn Omor’s time-first playbook: why London/New York kill zones align with predictable liquidity events, how he frames bias with daily narrative before drilling into entries, and where his “Power of Three” (accumulation–manipulation–expansion) shows up in real trades. You’ll see how he simplifies entries to retracements with safe invalidation, sizes dynamically through drawdowns, and stops chasing 1:5 fantasies in favor of high-probability targets that actually get hit. If you’re a newer trader trying to bridge the gap between SMC buzzwords and a repeatable strategy, this breakdown will give you the missing structure and discipline to execute.
Omor Playbook & Strategy: How He Actually Trades
Top-Down Bias: Frame the Story Before You Trade
You don’t need to predict the next candle; you need a working story for the day. Omor builds bias from higher time frames, then drills down until the path of least resistance is obvious.
- Start each day by marking D1 and H4 swing highs/lows and the weekly open line.
- If price is above the weekly open and taking out prior day highs, default to long bias; below and taking out prior day lows, default to short bias.
- Note the daily liquidity pools: previous day’s high/low, Asian high/low, weekly high/low. Those are magnets—label them “LQ.”
- Identify the “Power of Three” potential on D1: accumulation → manipulation (sweep) → expansion. Expect the sweep against your bias before the real move.
Time Advantage: Trade When Liquidity Is Predictable
Omor treats time like a technical indicator. Sessions concentrate liquidity; he only hunts when the market is most likely to move cleanly.
- Focus execution inside kill zones:
- London Open Window: 02:30–05:00 ET
- New York AM: 08:45–11:30 ET
- Stand aside the first 3–5 minutes of each window; let the opening impulse set the tone.
- If the day already expanded strongly during London, be pickier in NY—look for continuation pullbacks, not fresh breakouts.
- Avoid low-energy periods (post-NY lunch); no new entries after 13:30 ET unless managing an open runner.
Liquidity & Points of Interest: Where Price Is “Forced” To Travel
He doesn’t chase candles; he stalks liquidity and refined zones where risk is small and targets are obvious.
- Mark equal highs/lows, session highs/lows, and the daily open—expect sweeps before trend continuation.
- Define POIs on H1–M15: last up candle before a down move (bearish OB) or last down candle before an up move (bullish OB). Require displacement away from it to validate.
- Confirm a POI only if it aligns with a fair value gap (FVG) on M15–M5; overlap = higher probability.
- If price tags are a high-timeframe LQ and rejected into your POI/FVG combo, prepare for entry on the lower time frame.
Entry Blueprint: Keep It Mechanical
Entries are mechanical, so emotions don’t leak in. Omor waits for the price to come to him and uses the structure to define invalidation.
- Drop to M5–M1 at your POI. Wait for a liquidity sweep (wick through a local high/low) followed by a market structure shift (MSS) in your bias direction.
- Enter on the first retrace into the M1–M5 FVG that forms after the MSS; no FVG, no trade.
- Stop goes 1–2 ticks/pips beyond the swing that invalidates the MSS. If that level is too wide, pass and wait for a better setup.
- If the first pullback misses your limit by a hair, don’t chase; place a second limit only if a fresh FVG forms and the invalidation improves.
Targets That Actually Get Hit
He aims for logical exits connected to liquidity, not random R multiples. The goal is to get paid where others are forced to transact.
- First take-profit (TP1) at the nearest opposing liquidity pool (equal highs/lows, session high/low, or daily open).
- Second take-profit (TP2) at the next clean pool or the measured move of the expansion leg (project the impulse leg 1:1).
- If the price reaches TP1 in under 5 minutes, keep 50% on for a runner; if it grinds for 30+ minutes, tighten and be content with base hits.
- Never move a target farther once set; only scale out earlier if volatility collapses.
Risk & Sizing: Survive First, Thrive Later
Sizing flexes with drawdown and quality. He’d rather clip three A-setups small than swing big on a B-setup.
- Daily risk cap: 1R–1.5R max. If hit, stop trading for the day—no exceptions.
- Per-trade risk: 0.25R–0.5R in normal conditions; 0.15R during chop or news days.
- If you take two scratches or losers in a row, downshift size by 50% for the next valid setup.
- “Hard stop, soft target”: stops are always in the book; targets can be scaled based on real-time tape and session time.
News & Volatility: Respect the Calendar
News is not a reason to gamble; it’s a reason to control exposure. Omor times entries around scheduled impulses.
- Flat 2 minutes before high-impact releases (CPI, NFP, FOMC, central bank).
- Consider post-news plays only if an obvious sweep/MSS forms and the spread normalizes.
- On trend days following a major release, prioritize continuation pullbacks into FVGs during the next kill zone.
- If ATR (daily) is already >120% of its 20-day average by New York open, tighten targets—late moves tend to mean-revert.
Trade Management: Let Structure Lead
Once in, he manages against structure and time of day, not feelings.
- Move stop to breakeven only after an opposing swing is taken or TP1 is reached—whichever comes first.
- Trail below/above M5 structure on strong trend days; keep stop static on range days until TP1.
- If price re-enters your original POI without printing a new displacement, exit and reassess—your read may be early.
- One add-on max, and only after a fresh MSS + FVG in the trade direction.
Playbook Filters: Say “No” Faster
Most mistakes come from trading when the edge isn’t there. Omor uses hard filters to skip bad environments.
- Skip if D1 is inside day and Asia range < 40% of 20-day average—expect chop.
- Skip if the kill zone opens into the exact middle of a multi-day range—wait for range edge interaction.
- Skip if the first impulse of the session is directionless (overlapping bodies, no displacement).
- Skip the third trade of the day unless the first two were winners and A-quality.
Markets & Instruments: Pick Battles You Can Win
He focuses on where the microstructure matches the method. Beware instruments that fake you out.
- Prefer instruments with clean session behavior and tight spreads during kill zones.
- If spreads widen or the DOM gets jumpy at your entry, cancel and re-queue lower risk.
- Backtest your instrument’s average sweep size around session opens and place limits accordingly (e.g., 25–40% into the FVG, not the extreme).
Weekly Workflow: Pre-Plan, Then Execute
Preparation makes entries feel “slow and obvious.” The week is mapped before Monday’s bell.
- Sunday: Mark weekly high/low, weekly open, and prior week LQ pools; outline two directional scenarios with if/then notes.
- Daily pre-market (15–20 min): Update D1/H4 levels, define session plan: “Longs favored above weekly open into PDH; shorts below into PDL.”
- Post-session (10–15 min): Screenshot best setup taken or missed, annotate POI → sweep → MSS → FVG → targets; tag with reasons you pressed/hesitated.
- End of week: Export all trades, compute hit rate, average RR, and time-in-trade. If time-in-trade > 45 min median, reduce target distance next week.
Journal Metrics That Drive Improvement
He doesn’t guess what to fix—he measures it. A short metric stack keeps the feedback loop tight.
- Record for each trade: session, bias reason (one phrase), POI type, entry trigger, stop size (in ticks/pips), TP logic, and time-to-TP1.
- Track three rolling stats: win rate over the last 20 trades, average R per winner, and percent of trades taken in kill zones.
- If the win rate < 40% over 20 trades, restrict to only POIs that overlap with FVGs and align with the weekly open direction.
- If average R per winner < 1.2, push TP1 one liquidity level farther for the next 5 trades and reassess.
Mindset & Rules of Engagement
Discipline is built into the environment: your checklist, your clock, your screens.
- Maximum screen count: two. One higher-timeframe map, one execution ladder/chart; no social feeds during kill zones.
- “One market, one setup, one session”: select a single market for the week to reduce noise.
- If you break a rule (early entry, moved stop), log it and cut size by 50% on the next A-setup.
- End every day by rewriting tomorrow’s if/then statements in plain English so execution is binary.
Start With Risk: Size Positions to Survive Losing Streaks
Omor starts every plan with the downside, not the upside, and that single shift keeps him in the game when the market turns mean. He treats risk like a fixed cost of doing business—decided before entries, untouched during the storm.
He sizes positions so a cluster of losers can’t knock him off the week, and he scales down when volatility spikes instead of “earning it back.” Omor caps daily loss, limits concurrent exposure, and only presses size after clean, rule-based wins, never after frustration. He’d rather clip smaller wins for months than blow up in a single afternoon, and that restraint is the real edge. When your sizing respects streaks, you stop needing perfect calls—you just need consistent execution.
Let Volatility Lead: Adjust Exposure with ATR and Regime Shifts
Omor doesn’t force trades into the same box every day—he lets volatility set the rules. He checks the daily ATR and recent range compression to decide if he’s in expansion or chop, then tunes risk and targets to match. When ranges are tight, Omor trades smaller size, closer stops, and quicker targets; when ranges expand, he gives trades more room and lets winners breathe.
He also aligns entries with session energy: if ATR is already 100%+ of its 20-day average before New York, Omor downshifts and takes profits sooner. If the morning prints displacement and holds structure, he’ll permit a runner only while volatility remains elevated. The point is simple: volatility is the throttle, not your mood—Omor follows it, so his sizing and expectations are always in sync with the market.
Diversify Smartly: Mix Underlyings, Strategies, and Holding Durations
Omor spreads edge across uncorrelated places, so one idea can’t sink the boat. He rotates between a primary market and a backup instrument with different drivers, and he splits tactics between breakout continuation and mean-reversion pullbacks. When conditions favor trend, he leans on momentum structure; when the tape compresses, he shifts to fade setups with tighter targets. The aim isn’t to trade more, it’s to make sure the next trade isn’t just another version of the last.
He also diversifies by time: quick intraday plays during kill zones and occasional swing holds only when daily structure supports it. Omor caps total exposure across strategies so a bad hour doesn’t contaminate the day, and a choppy day doesn’t poison the week. He reviews correlations weekly; if two plays start moving together, he treats them as one risk unit. This way, diversification becomes a risk tool, not a buzzword—and Omor keeps his equity curve steadier while still letting skill compound.
Trade the Mechanics, Not Predictions: Rules Beat Opinions Every Day
Omor doesn’t try to guess tomorrow’s headline or call tops; he runs a checklist and lets the setup either qualify or fail. He wants a time window, a clean level, a displacement move, and a measured pullback—no four, no trade. If the market prints the sequence, he executes; if not, he does nothing, even when it “feels” like a runner is coming. The edge is the repeatable sequence, not the story in your head.
He pre-sets invalidation at structure, places targets at nearby liquidity, and manages the position only when price interacts with those markers. If the first pullback misses, Omor won’t chase—mechanics say wait for a new fair retrace or walk away. He logs whether each trade met every rule, so he can’t “remember it prettier” later. That’s how Omor keeps his P&L tied to process, not opinions.
Define Risk Upfront: Targets at Liquidity, Stops at Structure, Repeat
Omor starts with the exit and works backward—where are traders forced to transact, and where is the trade provably wrong? He anchors stops just beyond the swing that invalidates the setup and sets initial targets at the nearest opposing liquidity pool, so every trade has a clear “fail” and a realistic “get paid.” That makes reward a byproduct of structure, not hope.
Once price moves away from entry, Omor scales at TP1 and only trails behind fresh structure, never random distances. If the market grinds instead of expands, he takes the base hit and resets rather than letting a winner drift back to break-even. If price re-enters his entry zone without displacement, he’s out—no negotiations. Define the risk, choose the liquidity, execute the plan, and repeat until the process is boring—that’s Omor’s edge.
In the end, Omor’s edge isn’t a mystery indicator—it’s the discipline to let time and structure do the heavy lifting. He maps the day from the top down, respects the weekly and daily narrative, and then hunts inside specific kill zones where liquidity reliably shows up. Liquidity sweeps, a clear market structure shift, and a fair-value-gap retrace define his entries; stops live just beyond invalidation, and targets sit at obvious pools where traders are forced to transact. The goal is clean cause-and-effect: story → sweep → shift → retrace → payout.
Just as important, Omor treats risk like rent and volatility like the throttle. He sizes to survive clusters of losses, scales expectations to the day’s ATR, and refuses to chase when the tape won’t pay. Process beats prediction: if the checklist doesn’t print, he does nothing; if it does, he executes and journals it the same way every time. From blowing accounts to consistently funded payouts, his lesson set is simple and transferable—trade the clock, trade the mechanics, and let the math of disciplined repetition compound.
