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Otakar Suffner—the founder behind FTMO—sits down to share how a small Czech startup became a global home for funded traders. In this interview, he explains why FTMO’s evaluation design (Challenge → Verification) rewards discipline, why weekend flat rules matter, and how his own trading leans on probabilities instead of indicators. If you’ve ever wondered what prop firms look for, how scaling works, or why community and transparency are baked into their culture, this chat with Otakar is gold for ambitious traders.
In the piece below, you’ll learn the concrete rules FTMO uses to separate signal from noise, the statistical thinking Otakar uses to frame trades (e.g., targeting prior-day highs when odds favor a break), and the exact profit-split and scaling mechanics that make growth possible for funded traders. We’ll also cover why free trials and detailed account analytics are the best sandbox for proving your edge before you risk real capital, plus the operational details (brokers, platforms, support) that can make or break your experience.
Otakar Suffner Playbook & Strategy: How He Actually Trades
Core philosophy: bet with statistics, not opinions
Otakar Suffner treats trading like running an experiment. His focus is on collecting repeatable situations where the odds tilt your way and sizing them so a cold streak doesn’t kill the account. Prediction takes a back seat to risk math and sample size.
- Define your edge as a repeatable pattern with measurable expectancy (e.g., +0.20R to +0.35R per trade over 100+ trades).
- Track only a handful of contexts (e.g., break of prior day high/low after narrow range; session open drive; first pullback after trend day).
- Pre-declare the hypothesis for each setup: entry, invalidation, target, average adverse excursion (AAE), and average favorable excursion (AFE).
- Trade the same setup the same way every time for at least 30–50 trades before judging results.
- Avoid indicator stacking; one trigger, one filter, one exit plan is enough.
Risk rules that keep you in the game
He runs the account with hard, simple brakes so variance doesn’t spiral. Daily and overall loss caps force discipline, while a minimum activity rule keeps you honest about sample size instead of “one-hit wonder” wins.
- Set a hard daily loss cap (e.g., 1R–2R of your average risk) that auto-closes the platform for the day—no overrides.
- Set a hard overall drawdown cap (e.g., 8R–10R); if hit, stop trading and run a post-mortem before any restart.
- Require a minimum active trading window (e.g., at least 10 trading days per cycle) so results aren’t luck-skewed.
- Enforce consistency checks: if one day >35% of cycle profits, trim risk for the next three sessions.
- Go flat into weekends and major illiquid windows; widen stops or stand aside around scheduled high-impact news if spread/volatility models degrade your edge.
Finding and firing the actual trade
He favors clean, rules-based triggers you can code, journal, and audit. Context first (volatility and structure), then a single entry mechanism that fires without debate.
- Build a two-layer signal:
- Context: expanding volatility + directional bias (e.g., prior day range contraction → expansion day).
- Trigger: break-retest of level, or first pullback to VWAP/previous session extremes with tape confirming.
- Place the stop beyond the structure that invalidates the thesis (e.g., beyond the pullback low for trend-continuation entries).
- Predefine targeting logic: partial at 1R, move stop to breakeven only after AFE ≥ 0.7R, runner to next higher-timeframe level.
- If slippage/spread exceeds your model tolerance at entry time, cancel the order—edge deteriorated.
- Allow exactly one re-entry per idea if the structure remains valid; the second failure retires the setup for the session.
Position sizing, scaling, and cool-down
His sizing is volatility-aware and drawdown-aware. Size expands after equity milestones and contracts automatically during cold streaks. The goal is smooth compounding, not hero days.
- Risk a fixed fraction of equity per trade (e.g., 0.25%–0.50%); convert to units using current ATR or recent spread/volatility to keep stop distance realistic.
- Add dynamic throttles:
- After +4R cycle-to-date, increase risk by 10% for the next five trades.
- After −4R streak, cut risk by 50% and switch to A-setups only for the next five trades.
- Use a 2-strike day rule: two full-R losses in a session end trading; review and reset.
- Scale out mechanically: 50% off at 1R, 25% off at next key level, trail final 25% using structure (swing lows/highs).
- No martingale, no averaging down—ever. New idea, new trade.
Data, journaling, and decision audits
Everything gets measured. He leans on performance analytics to separate skill from noise and to prune or promote setups quickly.
- Journal entry/exit screenshots, rationale, emotions (1–5), execution grade, and any rule deviations.
- Maintain a setup scoreboard (by instrument, session, and volatility regime) showing win rate, average R, AAE/AFE, and time-in-trade.
- Cull any setup with expectancy < +0.10R after 100 occurrences or with a stress score (rule breaks) above 10% of trades.
- Run a weekly review: top three errors, top three improvements, and a single change to test next week (never overhaul everything).
- Promote best performers to Priority A (more allocation, first to scan each session); demote laggards to Priority B or bench.
Instruments, sessions, and execution hygiene
He curates a small roster of liquid markets and treats time-of-day like a setting on the strategy, not an afterthought. Clean execution beats fancy theory.
- Focus on 2–4 highly liquid instruments you can watch live (e.g., one index future, one FX major, one commodity); avoid illiquid exotics.
- Trade only two sessions where your setups statistically work (e.g., first 90 minutes of London and first 120 minutes of New York).
- Pre-build limit and stop templates for each setup so orders are one-click and consistent.
- Latency and spread checks at the open: if either exceeds your threshold, delay entries or skip the first rotation.
- Keep a “no-trade” list for days your edge historically underperforms (e.g., holiday half-days, month-end rebalancing).
News, gaps, and weekend policy
Operational guardrails matter as much as entries. He avoids conditions where the model’s assumptions (spread, slippage, depth) break.
- Stand aside or cut size to quarter risk during scheduled high-impact events unless you have a tested news-specific setup.
- If holding through a gap is part of your plan, pre-size for overnight risk using higher ATR and hard limits; otherwise, flatten before the close.
- For funded accounts, respect hold-time and news restrictions to avoid invalid fills or violations; if any constraint conflicts with your setup, skip the trade.
- After event spikes, wait for spread/volatility normalization (e.g., 5-minute average spread back inside your threshold) before re-engaging.
- Document any policy exception in the journal and review its impact at week’s end.
Psychology, pace, and process
He builds decision stamina with routine: fixed scan, fixed checklist, fixed stop-time. The result is fewer impulse trades and more high-quality reps.
- Use a pre-trade checklist (market regime, setup present, risk size, news window, spread OK, plan written).
- Cap yourself to a maximum number of executions per session (e.g., 3–5) to prevent tilt.
- Schedule a hard stop time each day; no “last trade” revenge entries after that line.
- Grade each session A/B/C on process only (followed rules = A), and let process grades drive next day’s size adjustments.
- Keep one metric for the month (e.g., % of trades executed exactly as planned) and aim for 85%+ before increasing risk again.
Size Risk First, Then Trade: Daily Caps, Two-Strike Stop
Otakar Suffner treats risk as the only lever you fully control, so you set it before you even think about entries. Start by fixing a small, repeatable R per trade and a hard daily loss cap that locks you out when hit. That cap keeps one bad morning from turning into a blown week. If your plan says 0.5% per idea and 1–2R daily max, you stop when the meter hits red—no exceptions.
His simple “two-strike” day rule ends tilt before it starts: two full losses and you stand down. This forces traders to protect the sample size and show up tomorrow with a clear head. Otakar Suffner also pairs caps with a preset cool-down, so you don’t sneak back in after a hit. The result is boring on purpose: consistent risk, contained drawdowns, and a survivable path to compounding.
Let Volatility Decide Position Size, Targets, And Session Selection
Otakar Suffner builds size around what the market is actually doing, not what he hopes it will do. When ATR and spreads expand, he cuts unit size so the same stop distance risks the same tiny R. When volatility compresses, he allows slightly bigger size or tighter stops to keep expectancy stable. Targets flex too: quiet sessions aim for quick 1R–1.5R takes, while trending volatility invites runners to higher-timeframe levels.
Session choice is volatility-led as well, and Otakar Suffner treats time-of-day like a parameter in the strategy. If the London open is choppy beyond thresholds, he waits for New York when his setup historically performs. If post-news spreads stay wide, he delays entries until they normalize to pre-defined levels. The edge comes from letting volatility set the pace, while you simply follow the math.
Diversify By Instrument, Strategy, And Timeframe To Smooth Equity
Otakar Suffner doesn’t rely on a single market or one “perfect” setup; he spreads risk across a few liquid instruments and uncorrelated ideas. That means pairing, for example, an index trend-continuation play with a mean-reversion scalp in FX, so one regime’s pain becomes another’s gain. He caps exposure per instrument and per idea, keeping any single bucket from dominating the P&L. When a market goes dead or hyperactive, a different instrument can still print, and the equity curve avoids violent swings.
Timeframe diversification is the quiet edge in his playbook. He’ll run a higher-timeframe bias map, then execute on a lower-timeframe trigger so both structural moves and tactical pulls contribute. If the day turns into chop, the intraday scalps handle the noise; if it trends, the swing runner pays the bills. Otakar Suffner also rotates focus based on correlation—adding or trimming instruments when they start moving as one—so “diversified” doesn’t become “duplicated.” The goal isn’t more trades; it’s a steadier curve with multiple, truly independent ways to win.
Trade Mechanics Over Predictions: One Trigger, One Filter, One Exit
Otakar Suffner keeps discretion to a minimum by hardwiring how a trade is found, validated, and closed. One trigger fires the entry (e.g., break–retest of a key level), one filter confirms context (e.g., session trend or VWAP alignment), and one exit plan handles profit and loss. By limiting choices, he removes the wiggle room where fear and FOMO creep in. The idea is simple: trade the plan, not the story in your head.
He also standardizes what happens after the click, so every execution looks the same on the chart and in the journal. Stops sit where the thesis breaks, partials come off at predefined R-multiples, and a trailing rule rides the rest—no freelancing. If the trigger misfires but the structure holds, Otakar Suffner allows exactly one re-entry; if that fails, the setup is done for the session. A tiny checklist—trigger present, filter aligned, exit scripted—keeps you honest and protects expectancy session after session.
Defined Risk Always; No Averaging Down, Scale Out Into Strength
Otakar Suffner builds every trade around a pre-declared maximum loss, so the downside is known before the order goes live. The stop sits where the idea is invalid, and it never gets widened to “give it room.” If price tags the stop, he’s out—no hedges, no martingale, no rescue missions. Averaging down is banned because it replaces probability with hope and bloats risk exactly when the edge is weakest.
Exits are designed to monetize strength, not weakness. Otakar Suffner takes a first partial at a fixed R multiple, then lets a portion run into the next higher-timeframe level so winners can pay for many small losses. The stop can tighten as the price confirms, but it never moves the other way. By capping loss and scaling out into momentum, he keeps expectancy positive without relying on hero trades.
In the end, Otakar Suffner’s message is straightforward: prove discipline inside a fair, rules-based evaluation and you’ll earn meaningful capital and a clear path to grow it. The two-phase process—Challenge then Verification—exists to surface traders who respect hard risk limits and can show consistency over time, not just one lucky streak. Those trading objectives are explicit: a maximum overall loss, a profit target, a minimum of ten active trading days, and at least roughly half of those days profitable—simple constraints that force process over hope.
He also emphasizes flexibility with responsibility: during the evaluation, you can trade your style, hold overnight, and even over the weekend, but once funded, you’re flat each Friday to avoid weekend event risk. That balance—freedom to express edge, guardrails to cap downside—carries into the live account via a clean profit split and structured scaling. Traders keep a significant share of profits and can see risk parameters increase on a regular schedule when conditions are met, turning consistency into a larger opportunity without blowing up risk.
Finally, Otakar Suffner’s culture is about ut breadth of methods, shared standards, and liquidity. In practice, that means a shop where algo, fundamental, and statistics-driven traders debate ideas, where DAX and other liquid markets are popular for their session structure, and where no single style is “the way”—only adherence to risk and repeatability. Pick a liquid instrument, define your rules, meet the objectives, and let the framework do the heavy lifting while you execute.
