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In this interview, discretionary price-action trader Samuel Kavanagh—founder of KB Trading in Glasgow—walks through the real story behind his rise from demo-account curiosity to running an in-person prop desk. Samuel matters to retail traders because he blends old-school tape-reading principles with modern, data-driven discipline: daily planning, rigorous journaling, and a culture of accountability that turns “being right” into “being consistent.”
You’ll learn the core of Samuel Kavanagh’s strategy: how he frames bias with higher-timeframe structure, applies discretionary entries across FX, indices, and metals, and sizes risk based on setup and asset statistics—then pressure-tests those ideas with five years of backtests before they touch live capital. We’ll cover his morning plan, journaling with performance metrics (strike rate, MAE, expectancy), the psychology that tames revenge trading, and what he looks for when backing traders at his prop desk—clear takeaways you can adapt immediately to tighten execution and improve consistency.
Samuel Kavanagh Playbook & Strategy: How He Actually Trades
Market Universe & Timeframes
Samuel Kavanagh trades a tight universe so he can recognize behavior fast: major FX pairs, indices, and a few metals. He built his reputation running a Glasgow prop desk, focusing on clean structure and repeatable execution instead of flashy forecasts—an approach that suits both solo traders and teams.
- Trade a small watchlist: 6–10 liquid markets (e.g., EURUSD, GBPUSD, DXY proxy via USD pairs, XAUUSD, US100, UK100).
- Primary map on HTF: mark weekly/daily swing highs/lows and value areas before London.
- Execute on intraday: 15m for setup formation, 5m/1m for trigger and risk placement.
- Only trade sessions you can statistically justify (e.g., London open to NY lunch); no “off-hours” boredom trades.
- Keep a “no-trade if” filter: unresolved news spike, ADR already exceeded, or overlapping HTF levels too close for clean R multiples.
Bias: From Higher-Timeframe Story to Today’s Plan
His bias comes from where price sits relative to HTF structure and prior day’s value—then he writes a one-page plan before screens. Traders following this flow avoid prediction traps and step into markets only when the story is obvious.
- Define HTF state first: trend, range, or transition. If unclear, tag “neutral” and reduce size.
- Draw the two nearest HTF decision points (supply/demand or prior day’s high/low) and trade between them.
- Pre-commit the session narrative in one sentence: “If price accepts above yesterday’s high, I’ll only look long on pullbacks.”
- Cap the number of scenarios to two; if a third appears, you’re forcing it—stand down.
Entry Triggers: Simple Price Action You Can Repeat
Sam favors discretionary price action that’s simple enough to execute at speed but strict enough to measure. Think rejection at a level, then a clean shift in order flow on the trigger timeframe.
- Enter on one of three triggers only: (1) rejection wick + engulf, (2) break-retest with close through level, or (3) failed breakout back inside range.
- Your trigger must form at a pre-marked level; never “find” setups after the fact.
- Wait for close: no early entries inside the signal candle.
- Invalidate fast: if the next candle prints beyond the invalidation wick/level, exit—no negotiation.
Risk & Position Sizing: Variance You Can Survive
His desk cultures risk first: consistent size, adaptive to instrument volatility, and hard daily loss limits so traders live to fight the next session. This is how a young prop desk stayed durable while scaling.
- Fixed % risk per trade (e.g., 0.25%–0.5%) with volatility filter: wider stops = smaller lots.
- Hard daily stop: 1%–1.5%. Hit it? Flat for the day—process review, not revenge.
- Max two losers in a row before a 30-minute reset; three losers = done for the session.
- Size from the stop, never from the feel: lots = (account × risk%) ÷ stop (in currency terms).
- For correlated instruments (e.g., EURUSD + DXY inverse), cap total “theme risk” to one trade’s risk.
Trade Management: Let the Stats Drive the Steering
Management is standardized, so the desk can measure expectancy across traders. The rules reduce tinkering and make P&LL swings tolerable while still capturing runs when the market trends.
- First target at 1R only if the day is choppy or ADR nearly met; otherwise, skip partials and target structure.
- Move to breakeven only after (a) close beyond the level and (b) fresh structure prints in your favor.
- Trail behind swing structure on 5m once price reaches 2R; no micro-managing on the 1m.
- If the HTF level is hit ahead of schedule, bank at least 70% and let a runner work to the next zone.
Journaling & Review: Where Edge Actually Compounds
Kavanagh emphasizes journaling with specific metrics and frank post-trade notes. This is the backbone of his firm’s coaching loop and why traders improve month to month, not just “trade and hope.”
- Track these five: setup tag, session, MAE (in R), MFE (in R), outcome (R), and compliance (Y/N).
- Weekly stat check: top two setups by expectancy; bottom one gets paused or re-defined.
- Screenshot before and after with plan vs. execution notes; grade discipline, not P&L.
- Build a “playbook ladder”: only add a new setup after 30 logged trades at ≥ +0.5R expectancy.
Prop-Desk Standards You Can Adopt Solo
Running a desk at 21 forced Sam to codify standards that translate well to any retail trader: structure the day, keep rules visible, and make performance review unavoidable.
- Morning cadence (timed): 10 min HTF map, 10 min levels, 5 min scenarios, 5 min risk checks; then silence until trigger.
- On-screen checklist: bias, level, trigger type, stop location, risk %, news filter—tick all or pass.
- “Green-light windows”: two 60–90 min blocks you trade with focus; everything else is admin/backtesting.
- End-of-day huddle (solo or with a buddy): two wins/one fix for tomorrow; log it before shutting down.
Building and Funding Traders: What He Looks For
Because he both trades and backs traders, his criteria reveal what actually matters: rule-following under pressure and a journal that proves the edge. The rest is window dressing.
- Minimum 100-trade sample on a single setup with positive expectancy and sub-1R average loss.
- Proof of drawdown control: maximum peak-to-trough ≤ 5R in the last 100 trades.
- Clear “kill switch” rules and evidence they were followed (days stopped early, trades skipped).
- Communication: daily plan posted before session, post-mortem after—no ghosting during slumps.
Psychology: Habits That Survive the Next 1,000 Trades
Kavanagh’s edge isn’t mystical—it’s how he behaves when the market gets loud. He trains habits that make discipline easier than impulse, so consistency becomes a default.
- Pre-commit three “if-then” rules (e.g., “If I feel FOMO, I step away for 5 minutes”) and log when they trigger.
- Use time-boxed focus: 50 minutes on, 10 off; avoid decision fatigue in slow tapes.
- No P&L during entries/exits—chart only. P&L view returns after the trade is managed to plan.
- One “fun trade” per week allowed at micro size; label it and never let it contaminate stats.
Career Path & Lifestyle Fit
He’s evolved from office floor to remote work and back again as life phases change, all while keeping the same playbook structure. Build your trading around your life, not the other way around.
- Choose an environment you can repeat daily (home desk vs. shared floor) and stick to it for 90 days.
- Protect your best hours for screens; push exercise, deep work, and recovery to specific time blocks.
- Scale capital only when process metrics (compliance ≥ 90%, weekly expectancy ≥ +0.3R) stay green for four consecutive weeks.
Branding Your Own Playbook (His Way)
Sam’s message: the trader is the edge; the system is a tool. Build a playbook you can prove in numbers, then expand it carefully as your competence grows.
- Start with one A-setup and one market; do 100 trades before adding anything.
- Write your rules where you can see them; if you broke one, tag the trade “DQ” regardless of outcome.
- Re-test quarterly: if a setup’s expectancy decays two reviews in a row, retire or re-specify it.
- Keep the business hat on: withdrawals on a schedule, tax bucket ring-fenced, and a monthly “owner’s memo” summarizing performance and plans.
The size risk is small, survival variance, compounded with consistent execution.
Samuel Kavanagh keeps the first lever simple: tiny fixed risk per trade, so one bad hour never nukes the week. He treats position size as math, not mood, and he scales it from the stop distance so every idea pays the same tuition. By staying small, he buys the right to see the next hundred trades and let the law of large numbers work for him. When the market whips, his size doesn’t; that’s how consistency beats hot streaks.
He also enforces a hard daily loss cap and a “two strikes then reset” rule to stop tilt before it starts. Small risk keeps the psychology quiet, which makes execution clean and repeatable across sessions. With that calm, Samuel Kavanagh compounds by showing up every day and letting a modest positive expectancy do the heavy lifting. It’s not flashy, but it’s the only way the curve keeps bending up without drama.
Build bias from higher timeframes, execute triggers only at the level.s
Samuel Kavanagh starts each session by reading the weekly and daily structure, so today’s plan is anchored to the bigger story. He maps the two nearest decision points—prior day’s high/low or clear supply/demand—and writes a one-sentence narrative like, “Above yesterday’s high, I only buy pullbacks.” That bias filters noise and keeps him from chasing mid-air candles. If the higher timeframe is unclear, Samuel Kavanagh tags the day neutral and automatically dials down risk.
Execution happens only at pre-marked levels, never in the middle of nowhere. He waits for the candle to close to confirm a break-retest, rejection-engulf, or failed breakout back inside range, then places the stop beyond invalidation, not “where it feels right.” If price wanders without touching his levels, nothing happens—and that discipline is counted as a win because it preserves expectancy. The result is a simple loop: higher-timeframe bias sets direction, levels define where, and the trigger decides when.
Let volatility set stops and size; cap daily drawdown hard.
Samuel Kavanagh treats volatility as the tape’s speed limit, and he sizes to it instead of forcing the market to fit his risk. Wider stops on fast days mean smaller positions; tighter stops on quiet sessions allow normal size, never oversized bets. He measures the typical swing or ADR and parks the stop beyond that noise ban, so valid trades aren’t clipped by randomness. Because the stop is volatility-aware, the R multiple stays comparable across days, keeping performance steady.
The other half is a hard ceiling on pain: hit the daily drawdown and Samuel Kavanagh is flat—no “one more” hero trade. That rule protects the equity curve from spiral days and preserves mental capital for tomorrow’s opportunities. He also uses a “two losers then reset” checkpoint to break streaks and re-center execution. Combined, the volatility-based stop, proportional size, and fixed daily cap turn chaos into a controlled environment where edge can actually show up.
Diversify by market and setup, not random trades or opinions.
Samuel Kavanagh spreads risk across a small basket of uncorrelated markets and a few proven setups, not across hunches. He’ll pair a trend-continuation play on an index with a mean-reversion fade on a metal or a clean breakout on a major FX pair, so one theme can’t sink the day. Each setup has its own rules for level, trigger, stop, and management, which keep outcomes driven by process rather than vibes. If two instruments are basically the same trade—like EURUSD long and DXY short—he treats them as one risk and picks the cleaner chart.
He also varies duration with intent: quick scalps during choppy sessions, swing holds only when higher timeframes align, and ADR isn’t spent. Samuel Kavanagh caps simultaneous positions and forbids overlapping setups that crowd the same narrative, protecting his R from stealth correlation. New plays enter the roster only after a 50–100 trade sample shows positive expectancy; until then, they’re benched. This way diversification isn’t “more trades”—it’s a curated mix that smooths the equity curve without diluting edge.
Journal metrics that matter—expectancy, MAE, compliance—then prune weak edges.s
Samuel Kavanagh treats the journal like mission control, not a diary. Every trade is tagged by setup and session, with expectancy calculated per tag, so winners aren’t hiding a broken idea. He tracks MAE to see whether stops are placed beyond normal noise or inside the chop. Compliance sits front and center—did he actually follow the plan—because a green P&L on a broken rule is still a red flag.
Each week, Samuel Kavanagh ranks setups by expectancy and immediately benches any tag that slips negative for a meaningful sample. He studies MAE patterns to adjust stop placement rather than widening randomly, and he uses screenshots to compare the plan versus execution. If compliance drops below a preset threshold, size auto-dials down until behavior improves. The result is a living playbook that gets sharper over time because weak edges are cut and strong ones get more capital.
Samuel Kavanagh’s edge isn’t a single pattern—it’s the system around the trade. He evolved from oversized bets to controlled, repeatable risk, settling on small, volatility-aware position sizes to protect the equity curve and keep psychology steady. That shift turned hot-and-cold streaks into durable consistency, reinforced by ruthless journaling: tagging setups, tracking MAE, tweaking rules, and even removing entire plays when expectancy slips. He pressure-tests changes by projecting equity curves over the next 200–500 trades, so improvements are measured, not imagined.
His daily cadence glues it together: plan at night on the daily close, arrive early, map levels across a defined watchlist, mark news, publish a concise plan, then execute only when price meets pre-planned criteria. That same structure carries onto the floor with juniors, where work ethic, coachability, and emotional balance matter as much as chart skill; he looks for people who can handle losing days without unraveling and who will show up long before the funding arrives. The culture is transparent, disciplined, and protective of newcomers—right down to public reminders about impostors in his name—because trust and process are the foundation for long careers.
