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Today’s interview features Franklin Lyembela—the UK-based swing trader known for building consistency across multiple prop firms—on the Desire To Trade podcast with host Etienne Crete. Franklin co-founded a community helping traders navigate funded accounts and credits, trading education, psychology, and strict risk rules for his turnaround. If you’re curious how a price-action purist (no indicators) scaled from early struggles to managing six- and seven-figure allocations, this conversation is a goldmine.
In this piece, you’ll learn Franklin Lyembela’s exact approach: a one-hour chart, price-action strategy that looks for momentum shifts into fresh trends, then rides continuation moves with tight, rules-based execution. He explains why he risks ~1% per trade, focuses on four FX pairs (AUDUSD, USDJPY, EURUSD, EURJPY), and uses journaling and backtesting to keep an edge. You’ll also get his playbook for prop-firm success—how to pick programs, adapt to risk parameters, handle the emotions of larger numbers, and why mentorship and psychology work (think “Trading in the Zone”) are the multipliers other traders skip.
Franklin Lyembela Playbook & Strategy: How He Actually Trades
Core Identity & Edge
Franklin Lyembela trades as a clean, no-indicator price-action swing trader. He keeps things simple on purpose: a narrow watchlist and one timeframe so decisions are quick, repeatable, and stress-free.
- Trades purely with price action (no indicators).
- Operates as a swing trader, not a scalper or high-frequency day trader.
- Keeps a focused watchlist of four FX pairs: AUDUSD, USDJPY, EURUSD, and EURJPY.
- Prioritizes “fits my data” over “trade everything”; he drops pairs that don’t test well.
- Builds conviction from backtesting and ongoing journaling—not hunches.
Timeframe, Session, and Chart Prep
He runs the entire process from a single timeframe to reduce analysis paralysis. One chart, one rhythm, one set of rules—this keeps execution crisp and avoids second-guessing.
- Uses the 1-hour chart for scanning, entries, and management.
- Pre-marks key swing highs/lows and obvious HTF levels visible on H1.
- Defines the day’s bias by whether price is making higher-highs/ higher-lows (bull) or lower-highs/ lower-lows (bear).
- Sets alerts at levels—no chart babysitting; returns when price is at his spot.
- If the structure is messy or overlapping, he skips and waits for clarity.
Set up: Structure Break With a Clean Pullback
The heart of his strategy is catching a fresh move after structure shifts. He waits for a break that shows intent, then a tidy pullback that lets him define risk cleanly.
- Bias first: only look long in a sequence of HH/HL; only look short in LH/LL.
- Need to see a decisive break of the last swing (clear body close beyond it).
- Wait for a pullback into a prior decision area (broken swing, clean base, or obvious micro-range).
- Look for a rejection/impulsive candle from that area to confirm continuation.
- If the pullback runs too deep and flips the structure back, the setup is invalid.
Risk: Fixed, Small, and Boring on Purpose
Franklin treats risk like a utility bill—set it and move on. One fixed risk per trade keeps him emotionally even and lets the math do the heavy lifting.
- Risk a flat 1% of account equity per trade.
- Stop goes just beyond the invalidation swing (not arbitrary pips).
- Only one active idea per pair; avoid stacking correlated risk.
- Place the order only when the level + trigger are present; no “anticipation entries.”
- If price tags the stop, he logs it and moves on—no revenge trades.
Trade Management & Targets
He’s not trying to predict the exact top or bottom—just the chunk in the middle after momentum turns. Management is preplanned, so he isn’t improvising mid-trade.
- Base targets on recent swing structure: target the next opposing swing or a measured move of the last impulse.
- Let winners work; don’t cut early without a rule.
- Move stop to breakeven only after price cleanly clears the origin of entry and forms a new swing in his favor.
- If momentum stalls at the first target and prints reversal cues, scale down or exit—rules over hope.
- No adding to losers; adds are allowed only if a new, separate setup forms after a fresh structure.
Watchlist Discipline & Adaptation
He keeps the universe small to learn the “personality” of each pair. If the data changes, he adapts—but he doesn’t chase every shiny thing.
- Trade only the four pairs that historically test well for the playbook.
- Review monthly stats per pair (win rate, MAE/MFE, average R).
- If a pair underperforms several cycles in a row, pause it and re-test.
- Reassess levels after major calendar events; structure resets trump old lines.
- Never widen stops to “save” a trade; invalidation is a binary line.
Execution Routine (Before, During, After)
Process is the edge. Franklin’s routine makes his actions predictable, even when markets aren’t.
- Before: mark levels, set alerts, define “if-then” entries and exits on the H1 chart.
- During: wait for the break + pullback + trigger; place orders and walk away.
- After: screenshot entries/exits, tag the setup type, and log reasons to keep/kill the pattern.
- Weekly: audit the journal for recurring mistakes and best-working conditions.
- Monthly: update a simple playbook checklist based on journal insights.
Prop-Firm Playbook
He treats prop rules as risk constraints to engineer around. Consistency beats sprinting; he optimizes for staying eligible and scalable.
- Keep a max daily loss line well inside the firm’s threshold (e.g., half of the rule).
- Use the same 1% risk, but cap concurrent trades so daily drawdown can’t trip limits.
- Avoid trading right into high-impact news if the firm penalizes intraday drawdowns.
- Withdraw or scale allocations only after hitting predefined equity milestones.
- If nearing a drawdown limit, stop trading for the day/week—protect the account first.
Psychology & Decision Hygiene
Confidence comes from rules that are simple enough to repeat under pressure. He designs the plan so execution feels boring—in a good way.
- Pre-commit to the setup checklist; no checklist, no trade.
- Keep a “mistake counter” and aim to reduce it each month (not just “make more R”).
- Use alerts to limit chart time and cut emotional micro-management.
- Accept that missing trades are fine; breaking rules isn’t.
- When in doubt, don’t trade—wait for the next clean break-pullback.
Build Consistency With One Timeframe And A Tight Price-Action Plan
Franklin Lyembela keeps his edge by stripping the chart down and deciding everything on a single timeframe. One rhythm means one set of rules, so he isn’t second-guessing entries when higher timeframes disagree. With price action only, he marks swing highs and lows, defines trend, and waits for the market to come to his levels. That simplicity reduces hesitation and creates repeatable execution, which is the foundation of his consistency.
By committing to one lens, Franklin Lyembela can track the same signals every day—break, pullback, confirm, execute. He treats invalidation as binary, placing stops beyond the structure that proves him wrong and moving on if tagged. The focus on clean structure also makes journaling sharper, since every trade is comparable against the same criteria. Over time, that feedback loop compounds into confidence and consistency that scattered, multi-timeframe hunting rarely delivers.
Risk One Percent, Place Stops At Structural Invalidation Only
Franklin Lyembela treats risk like a fixed utility bill—predictable and boring—so emotions don’t hijack the trade. He risks roughly one percent per idea, which keeps losing streaks survivable and position sizes consistent. That single decision pre-defines how much pain he can take, letting him focus on reading structure instead of watching P&L flicker. If the setup isn’t worth one percent, it isn’t worth trading.
Equally important, Franklin Lyembela anchors his stop to structure, not a random pip count. The stop lives just beyond the swing that would prove his thesis wrong, making the loss meaningful feedback rather than a guess. This keeps reward-to-risk honest because targets are set relative to real market pivots, not hope. When the stop is hit, the idea is invalid—he logs it and moves on, preserving capital and mental energy for the next clean setup.
Trade Momentum After Breaks, Enter On Clean Pullbacks And Rejections
Franklin Lyembela hunts for fresh momentum right after the market shows its hand with a decisive break. He waits for the price to push beyond a key swing, then lets it pull back to the decision area where trapped traders sit. That’s where he looks for a clear rejection—an impulsive candle off the level, a swift wick rejection, or a fast reclaim—that confirms continuation rather than guessing tops and bottoms. Entering there keeps risk tight and places the stop just beyond the invalidation swing.
By doing this, Franklin Lyembela avoids the noise in the middle of messy ranges and focuses on the part of the move most likely to trend. He doesn’t chase the first breakout spike; he wants the market to revisit the level and “prove” strength again. This approach naturally boosts reward-to-risk because entries are closer to structure while targets aim for the next opposing swing. If the pullback runs too deep or fails to reject, he passes—discipline over FOMO every time.
Diversify By Pair And Session, Not By Random Signal Chasing
Franklin Lyembela keeps a small, familiar watchlist and diversifies by when and what he trades—not by throwing darts at dozens of symbols. He groups pairs by behavior and session, then chooses the ones that historically move cleanest during his trading hours. That way, he spreads opportunity across distinct conditions while still knowing each pair’s “personality.” The goal is quality exposure, not more charts.
Instead of stacking three highly correlated ideas at once, Franklin Lyembela limits concurrent risk and rotates between pairs that aren’t likely to deliver the same outcome. He also respects session character: if London ranges are choppy for a pair, he’ll prioritize New York follow-through, or stand down entirely. This framework reduces duplicated losses and smooths the equity curve without diluting focus. Diversification is strategic—pairs and sessions—while entries still follow the same price-action rules.
Process Over Prediction: Journal, Backtest, Refine, Then Scale Funding
Franklin Lyembela doesn’t try to forecast the economy or call tops—he builds a repeatable process and lets the stats guide him. He journals every trade with setup type, context, emotions, and management notes, then reviews weekly to spot edge killers and edge keepers. Backtesting keeps him honest about which rules actually pay, and it gives him the confidence to skip anything off-script. The result is fewer “maybe” trades and more “this is my setup” executions.
With cleaner data, Franklin Lyembela refines rules in small, testable tweaks—entry trigger, stop placement, target logic—rather than rewriting the whole playbook. Only after consistency shows up in the numbers does he scale funding, keeping risk per trade constant while increasing account size. That way, the psychological shock of bigger numbers is tempered by muscle memory. Prediction is optional; process is mandatory, and the equity curve reflects that discipline.
Franklin Lyembela’s core lesson is radical simplicity powered by mentorship and relentless process. He credits a turning point to learning from experienced traders, then building his own rule set instead of copying someone else’s, which shifted him from “buy low, sell high” guessing to a structured, profitable approach. That mindset extends to psychology work he practices deliberately—rating himself on emotions like fear, confidence, and overtrading—so improvement isn’t left to wishful thinking. His framework boils down to three pillars that he reinforces with his team: strategy, risk management, and psychology—executed the same way, every day.
On the mechanics, Franklin keeps the watchlist tight, trades clean structure on a single timeframe, and risks about one percent with stops at structural invalidation—never arbitrary pips. He treats mentorship as non-negotiable (find one, then actually follow them), builds community learning into his routine, and reviews journals to refine rules before scaling size. The long game matters: he co-founded a trading community, aims to help others separate real edge from noise, and is methodically working toward managing larger private funds. The takeaway for traders is clear—pick one process you can repeat under pressure, measure it honestly, and let consistency, not prediction, compound your results.
