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This interview features Moritz Czubatinski—co-founder of Trades.com and the Edgewonk trading journal—speaking candidly about how he built a sustainable approach to performance. Filmed as a live session, you’ll hear Moritz explain his shift from full-time day trader to swing/position trader so he can protect time for family, health, and businesses. He’s practical, numbers-driven, and big on process: checklists, structured routines, and using journaling data to make decisions instead of vibes.
In this piece, you’ll learn the core of Moritz’s playbook: how to organize your trading day with simple to-do lists, why meditation measurably improves his session results, and how journaling plus Monte Carlo stress-testing keeps him calm through drawdowns. We’ll break down his favorite breakout patterns (think clean flat-top triangles), his weekend-only swing process, and how he sizes up positions when volume and fundamentals line up. It’s a blueprint for traders who want fewer decisions, smoother equity curves, and more life outside the screens—without dumbing down the craft.
Moritz Czubatinski Playbook & Strategy: How He Actually Trades
How he chooses markets and the timeframe
Moritz keeps the toolbox simple: liquid names, clean structure, and enough movement to pay for the risk. He favors swing trades that let him step back from the screen while still compounding steadily. The goal is fewer but better decisions.
- Trade only liquid symbols with tight spreads and robust volume during your active session.
- Focus on daily charts for signal, 4H/1H for timing; ignore lower timeframes unless liquidity and structure are exceptional.
- Keep a watchlist of 20–40 instruments; add/remove weekly based on trend clarity and ATR.
- Sit out chop: if the daily ATR is shrinking and ranges compress without direction, reduce size or skip.
- Avoid event landmines you don’t model (major earnings, top-tier macro) unless you plan the gap risk explicitly.
Routine that creates edge (planning beats prediction)
His edge is organization. Moritz pre-plans the week, sets traps for his setups, and journals everything. The routine turns randomness into repeatable work.
- Weekend: map levels, trends, and scenarios; tag A-setups vs. B-setups; prewrite entry/exit conditions.
- Daily premarket: 15–20 minutes to refresh levels, check volatility (ATR, range expansion), and mark “if-then” triggers.
- During session: execute only prewritten plays; no ad-hoc trades.
- Post-close: 10 minutes to log trades, emotions (1–5), rule adherence, and screenshots.
- Weekly: review KPIs, remove the bottom 10% of setups, double down on the top 10%.
The core setups he actually takes
He prefers simple, testable structures—especially clean breakouts from well-defined bases and orderly pullbacks into prior structure. The edge comes from alignment: trend + level + participation.
- Breakout: buy only above a flat base/high-tight flag that held at least 5–10 bars; no early entries.
- Pullback: buy the first pullback to a rising 20/50MA confluence that coincides with the prior breakout level.
- Require trend alignment across daily and 4H; if mixed, pass.
- Demand confirmation: range expansion bar or volume pop vs. 20-day average.
- Skip “messy” candles around the trigger (long wicks, overlapping bodies).
Entry triggers and invalidation
Entries are mechanical, invalidation is visible on the chart, and there’s always a place where he is flat-out wrong. That clarity keeps hesitation low and consistency high.
- Place stops where the pattern is invalid, not at round numbers (e.g., below base low or below higher-low pivot).
- Use stop-limit or stop-market orders; no “I’ll see how it feels” discretion.
- If price triggers but closes back inside the range on the same bar, consider a scratch per plan.
- One attempt per setup per day; don’t revenge-reenter unless a fresh structure forms.
- If slippage exceeds your plan by 0.5R or more, reduce the size or skip the next marginal trigger.
Position sizing that survives drawdowns
Moritz treats sizing as risk engineering. He sizes to volatility and keeps portfolio heat capped so several losers in a row don’t break the account—or his head.
- Risk per trade: 0.3%–0.7% of equity for swings; never exceed 1.0%.
- Volatility-adjusted size: position = (risk per trade) ÷ (entry–stop) with ATR used to sanity-check.
- Portfolio heat cap: total open risk ≤ 2%–3% of equity.
- Correlation filter: max 2 positions per highly correlated theme (e.g., USD pairs, semis).
- Equity curve circuit-breaker: at −5% from equity high, halve risk; at −10%, trade only A-setups.
Trade management: let winners work, kill losers fast
The plan defines what to do after entry, so emotions can’t freeload. Moritz scales out into strength when structure supports it and respects his initial stop to the tick.
- First scale at +1R or prior swing level; move stop to breakeven only after structure confirms (e.g., HL after breakout).
- Trail behind swing lows/highs or a multiple of ATR (e.g., 1.5–2.0× ATR on the timeframe traded).
- Do not widen stops—ever. If invalidated, exit and re-plan.
- If momentum stalls (inside-inside-doji cluster) near resistance, take partials and tighten.
- End-of-day hard rule: flatten any position that violates your timeframe thesis.
Journaling to quantifythe edge
Data beats memory. Moritz logs every trade with context and emotion so he can separate a good loss from a bad decision and see where the real edge lives.
- Record: setup tag, market regime, R planned/realized, screenshots, and emotion rating (1–5).
- Tag mistakes explicitly (late entry, early exit, size error); pay a “mistake tax” by reducing size next session.
- Track KPIs weekly: win rate, average R, expectancy, max adverse excursion (MAE), and rule-adherence %.
- Archive playbooks for your top three setups; refactor rules when win rate or MAE drift.
- Use equity curve plus MAE/MFE distributions to refine stops and targets over time.
Psychology and energy management
He treats mindset like any other input: planned, tracked, and iterated. Energy is an asset; protect it so decisions stay sharp.
- 5–10 minutes of breathwork or meditation pre-session; log the effect in your notes.
- No trades after two consecutive rule-breaks that day—end the session early.
- Define a maximum decision count (e.g., 5 trade decisions/day); decision fatigue is real.
- Pre-commit to a “boring is good” mantra: if nothing triggers, you did it right.
- Separate outcome from process in reviews: grade only what you controlled.
Risk events and news filters
He structures around known volatility inflection points rather than guessing them. If he can’t model the risk, he reduces it or steps aside.
- Flat or half-size through top-tier events relevant to the instrument (CPI, FOMC, earnings).
- Widening spreads/gaps disable new entries; wait for spreads and ranges to normalize for two bars.
- For earnings plays: entry only after first post-earnings base forms; no anticipatory bets.
- Use a calendar habit: tag events directly on your watchlist with color codes.
- If a surprise tape-bomb hits, exit first, analyze later.
Portfolio construction and exposure limits
A smooth equity curve beats a spicy one. Moritz limits concentration and staggers entries so a single theme can’t dominate results.
- Cap exposure per theme at 30% of portfolio; per single name at 15%.
- Stagger entries across days/timeframes to avoid correlated timing risk.
- If three positions are highly similar, keep only the two with the cleanest structures.
- Maintain at least 30% dry powder in uncertain regimes to capitalize on fresh breakouts.
- Rebalance winners monthly—trim back to original risk if volatility balloons.
Backtesting and forward-testing the rules
Before scaling, he pressure-tests ideas with simple stats and forward logs. The goal isn’t perfection; it’s confidence that rules behave across regimes.
- Define a minimum sample (e.g., 100 trades or 12 months) before rule changes.
- Monte Carlo your equity curve to estimate likely drawdowns; size so the 95th percentile is tolerable.
- Forward-test with half-risk for four weeks before promoting a tweak.
- Sunset any setup that underperforms for two consecutive review cycles.
- Keep a “graveyard” of retired rules with notes on why they failed.
What to do tomorrow morning
He always knows the next three moves because the list is written the night before. Clarity reduces stress and speeds execution.
- Write a three-line plan per A-setup: trigger level, stop location, first target/scale.
- Pre-place alerts at levels; let the platform call you to the screen.
- Confirm alignment (trend + level + participation) before arming orders.
- If plan conditions aren’t met, do nothing and re-assess after the close.
- End the day by logging adherence and prepping the next session’s top two plays.
Size every trade by volatility; cap portfolio heat to survive drawdowns
Moritz Czubatinski sizes positions so the dollar risk follows the market’s actual movement, not his mood. He defines risk from entry to invalidation, then lets ATR or recent range guide the position size so each trade risks a consistent fraction of equity. That keeps any single loser small, and a string of them survivable.
He also caps total “portfolio heat,” so multiple open trades can’t sink the ship at once. If several setups trigger together, he cuts individual risk or passes on the weakest theme to stay within a fixed heat limit. When the equity curve dips—say, down 5–10%—Moritz automatically scales risk down and trades only A-setups until he’s back in sync. The result: compounding feels steady, decision-making stays calm, and big drawdowns become rare rather than inevitable.
Trade simple breakouts and first pullbacks; skip messy low-quality structures
Moritz Czubatinski keeps pattern selection ruthlessly simple: clean bases that break on range expansion, and first pullbacks to structure in a trending market. He waits for obvious levels that everyone can see, then insists on confirmationa —strong close through the line or a decisive power bar. If the candles are full of long wicks, overlapping bodies, or random spikes, he passes without hesitation. The idea is to trade clarity, not cleverness.
On pullbacks, Moritz prefers the first retest into prior breakout levels or moving-average confluence, then looks for a tight, low-risk trigger. He avoids deep retracements that turn a trend into a coin flip and refuses to “anticipate” before price proves it. If momentum fizzles right after entry, he scratches fast rather than negotiating with hope. By staying picky about structure quality, he keeps win rate and average R healthier than chasing every squiggle.
Plan weekly, prewrite if-then rules, execute only A-setups without distraction.
Moritz Czubatinski runs on planning, not prediction. Each weeken,d he maps levels, tags A- and B-setups, and writes if-then statements so decisions are made before the heat of battle. Premarket, he refreshes those levels and commits to a tiny list of triggers that would make him act. When the bell rings, he’s following a script, not his latest hunch.
During the session, Moritz executes only A-setups and ignores everything else—no “almosts,” no FOMO swipes. He preloads alerts so the platform calls him to the screen, then checks the rule: if X happens, do Y, else do nothing. If a setup degrades, he cancels it and moves on; there’s always another day. After the close, he grades rule adherence first and P&L second, keeping the loop tight so next week’s plan gets sharper.
Diversify by theme and timeframe; limit correlated positions to protect equi.ty
Moritz Czubatinski spreads risk across themes and timeframes so one narrative can’t hijack his equity curve. He buckets positions by driver—macro dollar, energy, semis, China beta—and caps exposure per theme, trimming or skipping the third look-alike. If two charts rhyme, he keeps the cleaner one and parks the rest on the watchlist.
He also staggers entries so timing risk doesn’t cluster on the same day or session. A daily trend trade might live alongside a slower weekly swing or a tighter 4H pullback, each with separate stops and objectives. When correlations spike, Moritz reduces size or scales out to bring portfolio heat back in line. The message is simple: protect breadth, pace your bets, and let independent edges compound instead of doubling down on the same idea twice.
Journal every trade, review KPIs, Monte Carlo-test expectancy before scaling
Moritz Czubatinski treats journaling like a trading edge, not homework. Every position gets tagged with setup, market regime, planned R, and emotion score so he can separate a good loss from a bad decision. He reviews win rate, average R, MAE/MFE, and rule-adherence weekly to see which rules actually pay rent. If a setup slips, he edits the playbook or bins it—no nostalgia.
Before raising size, Moritz runs simple Monte Carlo simulations on his equity curve to estimate realistic drawdowns and worst-case streaks. He sizes so the ugly percentiles won’t break his psychology, then forward-tests tweaks at half-risk for a few weeks. Mistakes get labeled and taxed—reduce size next session after any rule breach to reinforce discipline. Screenshots capture context he’ll forget later, closing the loop between plan, execution, and review. Over t,ime the data trims noise, sharpens entries, and gives him the confidence to scale without guessing.
In the end, Moritz Czubatinski’s edge isn’t a magic entry—it’s the machine around it. He builds a strategy from the ground up by fixing trade management first, then iterating take-profits and stops across hundreds of reps until the rules feel like his own, not borrowed lore. He refuses to run with someone else’s “money printer” until he has tested it himself and seen the results with his own eyes, because confidence in a drawdown only comes from evidence you generated.
Day to day, Moritz treats routine as a performance tool: brief meditation, a written to-do list, and immediate journaling and review after the session. He even tags whether he meditated and filters results by similar market conditions, noting that performance is measurably better when he did the pre-session work. The takeaway is simple—stack small, repeatable habits and let them compound into edge.
Structurally, he likes clean uptrends that form flat-top triangles and break on volume, often exceeding pattern targets; when the company’s sales and earnings are strong, he’ll lean a bit more on position size. But the guardrails matter more than the pattern: he quantifies worst-case pain with Monte Carlo reshuffles of his trade history, keeps trading as long as drawdowns stay within those bounds, and hits the pause button to review if that threshold is ever exceeded. That’s how you stay in the game long enough for a well-built process to do its compounding.
