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Julian Lim sits down for a candid interview on the Desire To Trade podcast, sharing the unpolished reality behind his push from side-hustle to consistent trading income. No book deal, no hedge fund pedigree—just a determined retail trader who’s blown up, regrouped, and gradually built a repeatable process. His story matters because it reflects the path most traders actually walk: messy starts, expensive lessons, then clarity around rules, risk, and routine.
In this piece, you’ll learn how Julian thinks about money management first, builds a simple trend-following playbook (think moving averages and clear entries/exits), and tests it across 40–50 trades before sizing up. We’ll cover why sticking to one method beats chasing indicators, how journaling and demo-to-live transitions smooth the emotional ride, and the lifestyle edges few discuss—keeping expenses lean, protecting focus, and even getting spouse buy-in. By the end, you’ll have a practical blueprint you can start applying today: define rules, size conservatively, track everything, and give your edge time to work.
Julian Lim Playbook & Strategy: How He Actually Trades
Core Market Beliefs & Edge
Julian Lim keeps his playbook simple: ride clean trends, stay out of chop, and let math protect the downside. He focuses on repeatable rules that survive different market moods rather than predicting news or calling tops and bottoms. Here’s how he defines and protects his edge.
- Trade only when the 200-EMA is sloping and price is on the correct side (longs above, shorts below).
- Classify regime daily: “trend” if ADX(14) > 20 and higher-highs/ higher-lows (or lower-lows/lower-highs) are present; otherwise “range—stand down.”
- If two higher-timeframe candles (e.g., H4) close against your direction, treat the regime as suspect and cut risk in half until the trend reasserts.
Instruments, Timeframes & Tools
He concentrates on liquid markets that reward discipline and pay tight spreads. Timeframes are stacked, so higher-timeframe bias guides lower-timeframe execution. Tools are minimal on purpose to keep decisions crisp.
- Primary markets: major FX pairs (EURUSD, GBPUSD, USDJPY), gold, and one index future/CFD; never more than five symbols watched actively.
- Bias from H4; execution on M30 or M15; management decisions on M5 for precision only after entry.
- Indicators: 200-EMA (trend filter), 20-EMA (dynamic pullback), ATR(14) for stops/targets; no more than these three on the chart.
Setup & Entry Rules
Entries are built around pullbacks in the direction of the dominant trend. The goal is to buy value in uptrends and sell value in downtrends—never chase breakouts in thin liquidity.
- Long setup: in an uptrend, wait for a pullback into the 20-EMA with RSI(14) between 40–60; enter on the first bullish close back above the 20-EMA.
- Short setup: mirror rules—pullback to 20-EMA in a downtrend; enter on first bearish close back below the 20-EMA.
- If spread > 20% the stop distance on entry, skip the trade.
- Skip any setup formed within 15 minutes of a high-impact economic release; re-evaluate after the first full post-news candle.
Risk Sizing & Portfolio Exposure
Julian treats sizing like the main edge—entries are secondary without tight risk math. He caps exposure across correlated instruments to prevent one idea from nuking the week.
- Risk per trade: 0.25%–0.5% of account; never exceed 1% even after long winning streaks.
- Max simultaneous exposure: 1.5% across all open trades; count EURUSD and GBPUSD as correlated (0.5x overlap).
- If equity dips 3R from the recent high-water mark, cut per-trade risk to 0.25% until two net winners restore balance.
Stop Placement & Initial Targeting
Stops live where the idea is wrong, not where it “hurts less.” Targets are mechanical, so emotions don’t creep in when candles speed up.
- Initial stop: 1.5×ATR(14) beyond the pullback swing low/high (longs below swing low; shorts above swing high).
- First target: 1R; take off 50% at 1R, move stop to entry on the remainder only after a candle close beyond 1R.
- If the trade fails to reach 0.5R within three bars of your entry timeframe, reduce the position by one-third and keep the stop unchanged.
Trade Management: Trail, Add, Abort
Management is where consistency is won or lost. Julian prefers simple, rules-first adjustments, so he never “hopes” a loser back to breakeven.
- Trail the runner with a 2×ATR(14) chandelier stop on the execution timeframe after reaching 1.5R.
- Add once per trade only: on a second pullback to the 20-EMA that holds, with the same stop logic; added size must not push total risk above original R.
- Abort early if a full-bodied opposite-color candle closes through the 20-EMA and ADX(14) < 18 (trend deterioration).
Session Timing & Execution Windows
He avoids the noisiest hours and focuses on times when spreads are tight and follow-through is likely. Fewer trades, cleaner outcomes.
- Active windows: London first two hours and New York first two hours; no new positions in the last hour of New York unless already in profit.
- If the day’s ATR is fully traveled by the time you’re considering entry, skip—late entries have poor reward-to-risk.
- Maximum three fresh entries per day; after two losses, stop trading for that session.
Pre-Market & Weekly Prep
Preparation trims impulsive decisions. The plan is reviewed before the week starts and refined each morning with fresh context.
- Sunday scan: mark trend regime, key H4 levels (prior week high/low, session highs/lows), and no-trade zones (major news windows).
- Daily checklist: confirm slope and location vs. 200-EMA, mark 20-EMA touch zones, and write one sentence per instrument: “Bull pullback buy above X,” or “Range—skip.”
- Set price alerts 5–10 pips before planned levels; no chart staring.
Journal & Metrics That Matter
Julian tracks the few numbers that predict survival: R-multiple distribution, win rate per setup, and time-in-trade. The journal drives changes slowly, not overnight.
- Log every trade with a screenshot on entry, at 1R, and at exit; tag by setup (PB-20EMA-Trend, News-Fade—should be rare, etc.).
- Weekly review: compute expectancy per setup and prune any tag with expectancy < 0.1R over the last 40 occurrences.
- Track “discipline score” (0–5) per trade; if average drops below 4 for a week, reduce size by half the following week.
Psychology & Behavior Rules
He protects mental capital the same way he protects financial capital. Small systems break under big emotions, so the playbook installs circuit breakers.
- Two-strike rule: two consecutive rule violations end the session immediately; the next day starts with a written pre-trade script.
- After any 3R day, take the next session off screens and review the last 20 trades for rule drift.
- No social media, no PP&L window during open trades; display only price, position size, and stop/target.
Scaling Up & Time-Based Milestones
Size increases are earned by data, not vibes. Milestones keep growth measured and prevent overconfidence creep.
- Increase risk from 0.25% to 0.5% only after 80 trades with expectancy ≥ 0.25R and max drawdown ≤ 6R.
- Allow a second instrument (e.g., add gold to FX) after three consecutive profitable months with fewer than 6 total trading days.
- Withdraw 10% of profits monthly once equity is 20R above start—pressure drops when money is periodically realized.
Contingencies & Edge Protection
Markets change. Julian builds a fallback plan so the playbook bends before it breaks.
- If three weeks show ADX(14) < 18 on most watched instruments, switch to half-size and accept only A-setups that touch the 20-EMA exactly.
- If spread or slippage widens beyond your backtested assumptions for five trades in a row, pause and re-benchmark costs before resuming.
- Once per quarter, re-validate on the last 12 months: if win rate or average R drifts by >20% from baseline, run a paper-trade month to recalibrate before going live again.
Size risk first, trade small until the edge proves itself
Julian Lim is blunt about this: position size is the first decision, not the last. He starts every trade by deciding the maximum dollar loss he’s willing to take, then sizes the position to fit that number—never the other way around. That simple order of operations prevents one bad candle from wrecking the week. It also forces patience, because small size makes you focus on the process instead of dreaming about outsized wins.
He recommends proving your edge with tiny risk until the data says “scale.” That means risking a fraction of a percent per trade, tracking R-multiples, and only increasing size after a statistically meaningful sample shows positive expectancy. When the account dips or your discipline slips, Julian cuts size automatically to reduce pressure. By treating size as a circuit breaker, he keeps the strategy alive long enough for the math to work.
Use volatility-based stops and targets to standardize reward-to-risk
Julian Lim wants your stop size to reflect the market’s current “breathing rate,” not your hopes. He leans on ATR so a quiet session gets a tighter stop and a wild one earns more room, keeping each trade’s R comparable. Stops sit beyond the structure that invalidates the setup, then are buffered by an ATR multiple to avoid normal noise. Targets are also expressed in R, so he can judge performance by expectancy instead of raw pips.
In practice, Julian calculates risk per trade first, converts that into position size from the ATR-derived stop distance, and then sets initial take-profit at a clean multiple like 1R or 2R. If the price reaches 1R, he scales or locks break-even, so randomness can’t turn a winner into a loser. When volatility compresses, he tightens the stop logic automatically; when it expands, he accepts wider stops without changing the dollar risk. This keeps decision quality steady across regimes and makes every trade comparable in the journal.
Diversify by pair, timeframe, and setup, not by random trade.s
Julian Lim warns that taking five trades on the same idea isn’t diversification—it’s leverage in disguise. He spreads bets across uncorrelated pairs, so a USD shock doesn’t hit every position at once. Timeframe staggering matters too: an H4 swing and an M15 intraday can coexist without stepping on each other. He also diversifies by setup type—trend pullback versus momentum continuation—so one market condition doesn’t sink the whole day. This mix reduces variance and keeps his equity curve smoother when a single theme cools off.
In practice, Julian caps total exposure to any one currency theme and limits duplicates of the same setup on correlated pairs. He rotates focus: if EURUSD fires a pullback long, he avoids cloning it on GBPUSD unless the structure is materially different. He also avoids stacking trades that share the same invalidation level or news risk window. By diversifying with intention—pair, timeframe, and setup—he keeps risk spread out and progress steady.
Follow mechanical entry rules; avoid prediction, news-chasing, and FOMO impulse.s
Julian Lim builds entries like a checklist, not a hunch. Trend filter aligned, pullback confirmed, trigger candle closes where it should—then he acts; if any box is missing, he passes. The clarity kills hesitation because the decision is either “on” or “off,” not “maybe.” Mechanical rules also make backtesting meaningful, which keeps him from reinventing the system after a random loss.
Prediction is banned: Julian doesn’t “feel” tops or bottoms; he executes signals. He avoids trading within minutes of major news and refuses to chase a candle that’s already run beyond his planned stop-to-target math. If he misses the entry, he waits for the next qualified setup instead of forcing it. That discipline keeps emotions out of the seat and lets the strategy—not fear or greed—do the heavy lifting.
Protect discipline with session limits, journaling, and predefined abort conditions.
Julian Lim treats discipline like capital—once it’s spent, results crumble. He sets clear daily limits: a max number of new trades and a cutoff after two consecutive losses to stop tilt. Every session starts with a short written plan and ends with a journal entry that scores rule-following, not just P&LL. This routine keeps him anchored when markets bait impulsive decisions.
Predefined abort conditions do the rest. If a candle closes decisively against the setup or spreads beyond assumptions, Julian closes early without debate. He also pauses new trades after a 3R day and reviews screenshots to spot the exact mistake patterns. By combining firm session limits, a simple journal, and non-negotiable exit triggers, he keeps his process clean and his edge intact.
Julian Lim’s core lesson is that survival comes from sizing first and letting the strategy breathe. He treats risk like a thermostat: set the max heat you can handle, then size positions to fit that limit—never the other way around. From there, he standardizes decisions with volatility-aware stops and targets so every trade speaks the same language in R. That makes results comparable, removes the “vibes,” and protects him when markets shift from calm to chaotic overnight.
He also diversifies with intention—by pair, timeframe, and setup—so one theme can’t sink the whole day. Entries are mechanical and checklist-driven, which kills hesitation and the urge to predict headlines. When conditions deteriorate, he leans on predefined abort rules, tight session limits, and a simple journal that scores discipline as seriously as P&L. Put together, Julian’s approach is a practical blueprint: keep size small until the numbers prove your edge, trade the trend with ATR-shaped risk, spread exposure intelligently, execute rules without drama, and let consistent behavior compound into consistent returns.
