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This interview features Ali Khan—an ICT-mentored, chart-obsessed trader—sitting down in Dubai to unpack how he actually thinks about the markets. He’s not selling fluff or psychology soundbites; he’s an in-the-weeds technician who studied Michael Huddleston’s ICT concepts for years and distilled them into a practical, repeatable approach. If you’ve heard “ICT” tossed around online but never understood what a serious practitioner does day to day, this is your gateway.
You’ll learn why ICT is a framework—not a single strategy—how to build a simple model around one or two core ideas (fair value gaps, order blocks, timing), and how to layer risk management with partials at logical levels. We cover aligning higher-time-frame bias with intraday execution, using time-of-day and news as catalysts, and setting constraints to curb overtrading—so you can move from “reading price” to actually trading it. Whether you’re new or pivoting from retail indicators, this conversation translates complex ideas into beginner-friendly steps you can use immediately.
Ali Khan Playbook & Strategy: How He Actually Trades
Core Market Focus & Instruments
Ali keeps his universe tight so he can recognize patterns fast and cut noise. Here’s how he chooses what to trade and when, so his attention stays on clean, repeatable setups rather than chasing every move.
- Trade 1–3 instruments only (e.g., GBPUSD, NAS100, or Gold) until your win-rate is stable for 90 days.
- Avoid overlapping instruments that react to the same driver (e.g., EURUSD + DXY conflict).
- Pre-filter days: skip your instrument if the daily ATR has compressed >25% vs. its 20-day average or if the calendar shows tier-1 events in the next 15 minutes.
- Only trade during your instrument’s “engine” session: London for GBP pairs; New York for US indices; overlap = A-setups only.
Higher-Timeframe Bias → Intraday Execution
He starts top-down: a clear map from higher timeframes, then hunts precise entries on the lower timeframes. This prevents “chart zooming” from changing the story mid-trade.
- HTF scan: mark weekly/daily swing highs/lows and the most recent displacement leg; note premium/discount relative to the current leg’s 50%.
- Bias rule: if price is in a discount relative to the last bullish impulse and forming higher highs/higher lows on H1, only look for longs intraday (and vice versa for shorts).
- Confluence minimum: require two of three—HTF level, session timing, and liquidity feature (equal highs/lows, prior day high/low, previous week levels).
- If HTF bias is unclear, label the day “exploratory”—risk is cut by 50% and only one trade is allowed.
Liquidity Map & Levels That Matter
Ali frames the day around where liquidity likely sits and how it’s harvested. You’ll stop forcing entries once you get systematic about where the market wants to go first.
- Pre-session markups: yesterday’s high/low, Asia high/low, weekly open, and any obvious equal highs/lows on H1/H4.
- Expectation rule: first sweep > then move. If London sweeps Asia high, look for New York continuation back into the main HTF leg.
- Do not fade fresh displacement. Wait for a retrace into the origin of the move (order block/imbalance) aligned with bias.
- Cancel the plan if price fails to react at your first HTF level—don’t “find” a new level mid-session.
Fair Value Gaps (FVG) & Order Blocks (OB) — How He Actually Uses Them
These tools aren’t magic; he uses them to define risk and timing. Think “mechanical anchor,” not “signal.”
- FVG entry zone = 33–66% of the imbalance, never the full gap; reduce slippage and avoid front-running.
- Valid OB must precede displacement and break a structure point; ignore passive consolidations.
- If both OB and FVG align, choose the one that gives the tighter stop while still sitting inside discount/premium logic.
- In trend, use the first mitigation; in chop, wait for the second touch or skip entirely.
Time-of-Day Triggers
Session timing is a huge edge for Ali. He narrows execution to predictable windows so outcomes cluster and data stays clean.
- London kill-zone: first 90 minutes after London open—look for the day’s initial sweep and directional set.
- New York kill-zones: pre-NY open 8:30–9:30 ET for data sweeps; equity open 9:30–10:30 ET for momentum follow-through.
- Stand down 3 minutes before and after tier-1 releases unless your plan explicitly targets the release wick.
- No new entries after 11:15 ET; afternoon trades require HTF news catalysts only.
Entry Model — From Idea to Trigger
Ali reduces “feel” by checking a short, fixed list before clicking. Replicate the checklist and your entries will look the same week after week.
- Ingredients required: HTF bias, liquidity event (sweep/clean break), location (OB/FVG in discount/premium), and a lower-TF confirmation (shift in market structure on M1–M5).
- Confirmation = break of the last counter-trend swing plus one clean pullback; no break, no trade.
- Place stops beyond the invalidation swing (not a fixed pip count); if that’s >1.2× your typical risk, skip the setup.
- If the entry candle’s body >50% of the day’s ADR fractionally, use limit-style at 33–50% retrace or pass.
Risk, Sizing & Drawdown Guardrails
His risk rules are designed to survive long enough for edge to show. The goal is consistent deployment, not max size.
- Risk per trade: 0.5R base on A-setups, 0.25R on exploratory days; never stack beyond 1.5R total exposure.
- Daily loss stop: −1.5R; weekly hard stop: −3.5R with mandatory review before resuming.
- If two consecutive losses occur in the same session, stop trading that session for the day.
- Reduce size by 50% after any −3R trailing drawdown from the last equity peak; restore after two green days.
Taking Profits — Paritals with Logic
He doesn’t guess targets; he ties them to liquidity and range. This helps bank gains without killing runners.
- TP1 at nearest opposing liquidity (e.g., prior day high/low or intra-day equal highs/lows) for 30–50% off.
- Move stop to breakeven once TP1 prints or after a 1R move—whichever comes first.
- TP2 at session range projection: use 0.8× of the 20-day ADR from session open if momentum is clean.
- Let 10–20% trail behind a structure stop (last swing) only if HTF leg remains intact.
Managing Trades in Real Time
Execution doesn’t end at entry. Ali follows a few simple “if-this-then-that” rules so emotions can’t rewrite the plan.
- If an opposite FVG prints against your position and holds two closes on your entry timeframe, cut to half size.
- If price closes beyond your HTF invalidation level, exit—don’t renegotiate.
- If the session ends and your runner hasn’t hit TP2, close 50% and trail the rest with the last swing.
- No adding to losers. Ever.
News & Catalyst Play
News is context, not a prediction engine. He uses releases to time sweeps and entries, not to guess numbers.
- If a release aligns with your bias, plan for a fake-out wick into your level; pre-place a limit only if your stop is naturally beyond that wick range.
- Skip first-touch post-news entries unless displacement confirms and the wick is reclaimed on close.
- Avoid trading thin calendars that still produce erratic moves—if liquidity is poor (holiday, end-month), sit out.
Journal, Stats & Review
Ali treats journaling like R&D, not homework. The point is to find what clusters into edge and delete everything else.
- Tag every trade with: session, setup type (sweep→MSH/MSL→FVG/OB), risk, R outcome, and screenshot.
- Weekly: export stats and rank setups by expectancy; only scale size on the top two performing tags.
- Kill any setup tag with rolling 20-trade expectancy <0 or a hit rate <35% unless R multiple >2.
- Keep a “skip list” (days/conditions that hurt you) and check it before each session.
Psychology That’s Actually Practical
No mantras—just rules that cap impulse. Keeping these tight makes the rest of the plan work.
- Pre-commit to max number of clicks per session (usually 1–2).
- Use a visible timer during kill-zones; if no setup triggers by the end, shut charts.
- After any FOMO entry, impose a 24-hour reset (charts view-only, journaling only).
- Trade from one watchlist layout and one execution template; moving windows = moving rules.
Building the Weekly Plan
He scripts the week before it starts. Structure beats vibes.
- Sunday map: mark weekly/daily levels, pick two instruments, write the If-Then scenarios for both directions.
- Choose your A-setups for the week in advance; everything else is a pass unless HTF displacement prints.
- Pre-schedule “no trade” windows (meetings, workouts); protect energy to protect discipline.
- Review last week’s worst decision and add a single guardrail to prevent its repeat.
Rapid Onboarding Checklist (Run This for 10 Trading Days)
If you’re new to this style, start small and track tightly. Ten days is enough to see whether the model fits you.
- Trade one instrument and one kill-zone.
- One setup only: sweep → market-structure shift → FVG/OB in bias direction.
- Fixed risk 0.25R, TP1 at nearest liquidity, TP2 at session projection; no mid-trade edits.
- Journal daily with screenshots; after day 10, keep what worked, drop what didn’t, and either repeat or scale to 0.5R.
Size Risk First: Fixed R, Scale Only When Stats Confirm
Ali Khan insists that risk sizing comes before entries, analysis, or conviction. He defines a fixed R (risk per trade) and treats it like a non-negotiable line item—no “gut” bumps because a setup looks pretty. Until a setup tag shows real expectancy in his journal, it stays at the base unit; only the data unlocks size. This keeps losing streaks shallow and prevents one bad day from wrecking the month.
When a tag passes his thresholds—sample of 20+ trades, positive expectancy, and stable drawdown—he scales in half-steps, not leaps. If performance slips below target hit-rate or expectancy, he instantly downshifts size back to baseline. Ali Khan’s rule is simple: your stats are your throttle, not your feelings. That discipline turns risk into a system, not a guess.
Trade With Volatility: ATR-Based Stops, Adaptive Targets, Session Filters
Ali Khan builds every trade around current volatility so his risk and targets breathe with the market. He sets initial stops using a multiple of ATR on the execution timeframe, then confirms they sit beyond the invalidation swing—not a fixed pip guess. If ATR is elevated, he narrows trade frequency and widens stops with smaller position size; if ATR is muted, he tightens stops and requires cleaner structure to avoid chop.
Targets flex too: TP1 aligns with the nearest opposing liquidity, while TP2 references a fraction of ADR or session range so he isn’t asking price to do more than the day can deliver. Ali Khan only executes inside predefined “engine” windows—London or New York kill-zones—because that’s when realized volatility tends to cluster. He stands down around tier-1 releases unless he’s explicitly playing a wick reclaim. When ATR compresses hard versus its 20-day average, he either reduces risk by half or skips the day entirely, letting volatility come back to him.
Diversify By Instrument, Strategy, And Timeframe To Smooth Equity
Ali Khan spreads risk across a small basket of uncorrelated edges so one market’s mood swings don’t dominate his P&L. He keeps two primary instruments plus a backup that moves on different drivers, and he rotates attention based on which has the cleanest structure that week. Within each instrument, he runs at least two distinct playbooks—trend continuation and sweep-reversal—so he isn’t hostage to a single market regime.
Time diversification is just as deliberate for Ali Khan: he aligns higher-timeframe bias (daily/H4) with intraday execution (M5/M1) to avoid random entries that fight the big picture. If the higher timeframe is choppy, he downshifts to a single session and one setup to reduce variance; if it’s trending, he allows a second attempt only when the structure fully resets. He limits total concurrent exposure to 1.5R across instruments and never doubles the same idea in two correlated markets. Equity smooths out not by adding noise, but by adding truly different bets.
Prioritize Mechanics Over Prediction: Liquidity, Timing, and Repeatable Execution Checklists
Ali Khan treats forecasting as a trap and mechanics as the edge. He maps where liquidity sits—prior day high/low, Asia range, equal highs/lows—and waits for a sweep before even thinking about entry. Then he syncs entries to session windows so the move has fuel, not just a pretty level. His checklist forces the same steps each day: mark levels, define bias, identify the sweep, confirm a shift, execute or pass.
If any box is unchecked, Ali Khan stands down, no matter how tempting the candle looks. He wants a break in counter-trend structure plus a clean retrace into an FVG or OB; without both, it’s prediction, not process. Stops go beyond the invalidation swing, not an arbitrary pip count, and targets tie back to opposing liquidity or a realistic session range. The goal isn’t to be right early; it’s to be mechanically consistent so the market pays out when conditions align.
Choose Defined Risk Setups; Avoid Unlimited Downside And News Whipsaws
Ali Khan builds every idea around a clearly defined worst-case number before he even thinks about targets. He never averages down, never widens stops, and never leaves a position naked into tier-1 news unless the plan is explicitly a wick-reclaim play. If a setup can’t be framed with a hard stop beyond structural invalidation and a pre-planned position size, it’s off the menu—no exceptions. Unlimited downside is not a personality trait; it’s a math error.
When volatility spikes, Ali Khan reduces size and increases distance to the structural stop so the risk stays constant in R terms. He refuses to stack multiple correlated positions that would multiply the same downside outcome, and he cuts exposure to zero when an opposite FVG forms and holds on his execution timeframe. Into major releases, he flattens or sets a conditional entry that triggers only after displacement confirms; guessing numbers is gambling. Defined risk keeps him in the game long enough for edge to show, and that—more than any hot take—is why his equity curve survives.
In the end, Ali Khan’s message is disarmingly simple: edge lives in mechanics, not in prediction. He treats ICT as a framework for reading algorithmic price delivery—not a single, magic “ICT strategy”—and then builds a tight playbook around liquidity, timing, and structure. Sessions provide fuel, liquidity pools provide targets, and displacement provides the cue; everything else is optional. Risk is pre-defined in R, not vibes, and position size flexes with volatility so the same thesis doesn’t secretly carry different danger on different days. He journals like a scientist, promotes setups only when a tag shows positive expectancy, and cuts size the moment the stats slip.
What makes his approach durable is how the parts lock together. Higher-timeframe bias narrows direction, sweeps create opportunity, an FVG or OB anchors risk, and a lower-TF shift in structure flips the trigger—always inside the day’s realistic range. Targets map to opposing liquidity or session projections, partials bank progress, and runners live only while the higher-timeframe leg stays intact. He won’t stack correlated bets, won’t add to losers, and won’t trade outside kill-zones unless a catalyst justifies it. Ali Khan keeps the playbook small, the rules specific, and the feedback loop fast—so the market can pay him for discipline, not for guessing.
