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In this interview, trader and former fund manager Alexander Douedari explains how he moved from painful early losses to running rule-based, professional money—emphasizing statistical edge, consistency, and accountability. He’s refreshingly blunt about the myths retail traders buy into, why institutions obsess over process, and how a verified multi-year track record north of 110% with ~10% max drawdown comes from boring discipline, not flashy screenshots. If you’re new, this is the kind of strategy conversation that cuts through hype and gets you focusing on what actually compounds.
You’ll learn Douedari’s “process over results” framework: build a rules-based trader strategy with positive expectancy, backtest to get a real sample size, simulate to close the gap to live, and size risk so losing streaks don’t spiral—then scale down when you drift outside your data and ramp up when you’re back in rhythm. He separates psychology from edge (fix the system first, then your mindset), shows how market phase and time-of-day matter, and explains why copying someone else’s playbook fails unless it fits your personality and schedule. By the end, you’ll have a clear blueprint to journal the right things, grade setups, avoid overtrading, and think like a pro while keeping the beginner-friendly steps simple enough to apply today.
Alexander Douedari Playbook & Strategy: How He Actually Trades
Core Philosophy: Process First, Results Follow
The goal is repeatability. That means a clearly defined edge, run with discipline, sized so that losses are survivable and gains compound. This section lays out the non-negotiables that shape every decision before charts even come up.
- Define your edge in one sentence; if you can’t, you don’t have one.
- Trade only 1–3 setups you can describe with objective if/then rules.
- Aim for positive expectancy: target win-rate × average win ≥ 1.2 × average loss.
- Hard rule: if a trade doesn’t match a written setup, it’s not taken—no exceptions.
- Limit active markets to a maximum of 3 at a time to preserve focus and data quality.
- Keep risk constant in R-multiples (risk units), not dollars or lots.
Market Regime & Time-of-Day
Edge lives and dies with context. Identify whether the market is trending, ranging, or transitioning, and align entries with the time windows where follow-through is statistically most likely.
- Classify regime daily:
- Trend: price above/below 20 & 50 EMA with aligned slope and higher highs/lows or lower highs/lows.
- Range: 20 EMA flat, price rotating around VWAP or yesterday’s mid.
- Trade your setups only in matching regimes; if regime shifts mid-trade, manage out per plan.
- Define “prime hours” per instrument (e.g., FX: London open + first 2 hours; US indices: cash open + first 90 minutes).
- No new trades in the last 30 minutes of your session unless in a pre-defined news setup.
- If ATR(14) is in the bottom 30% of its 6-month range, favor mean-reversion; top 30%, favor continuation.
Set Up Library: Exactly What You Trade
Keep it simple: one continuation and one mean-reversion setup per market. Name them, grade them, and execute them the same way every time.
- Continuation (“Pullback to Value”):
- Regime = trend; price pulls to 20 EMA/VWAP; confluence with prior day high/low or session IB edge.
- Entry on rejection candle or structure break; stop beyond pullback extreme; target = 1R to scale, runner to 2–3R if structure holds.
- Mean-Reversion (“Failed Break Fade”):
- Regime = range; price wicks outside prior range by ≥0.5× ATR(14) and closes back inside.
- Enter on the first pullback to the breakout level; stop beyond the wick extreme; target = range mid then opposite band.
- Minimum signal quality: require 2+ confluences (e.g., EMAs + level; VWAP + session high/low).
- If news > “medium impact” within 15 minutes, skip all mean-reversion entries.
Risk & Trade Management
Sizing and exits keep you solvent. This framework ensures losers stay small and winners are allowed to breathe.
- Risk 0.25–0.5% of account per trade; never exceed 1% in aggregate exposure.
- Daily loss cap = 1% or 2R (whichever comes first); hit it and stop trading for the day.
- Place stops where the setup is invalidated, not at round numbers; never move a stop further away.
- First scale at +1R (take 30–50% off), move stop to breakeven only after structure confirms (e.g., higher low forms).
- Trail runner using the last swing structure or a 20-period EMA close; exit on opposite signal or EOD rule.
- If spread or slippage exceeds 20% of the stop size, reduce the size or skip the trade.
Execution Workflow: Before, During, After
Consistency is a checklist. This section turns preparation and review into muscle memory so your best trade looks like your last one.
- Pre-market (15 minutes): define regime, mark levels (previous day high/low, session open, VWAP, IB range), note news, set alerts.
- Pre-trade (1 minute): confirm setup name, confluences ≥2, R multiple, stop distance, and risk size—say it out loud or write it.
- During trade: no adding unless a planned add-on trigger (e.g., second pullback) hits; max 1 add with half initial size.
- Post-trade (2 minutes): log result in R, reason to enter/exit, emotion (1–5), and one lesson.
- End of session: screenshot A-quality setups (taken or not) and tag them for your playbook.
Data, Backtesting & Simulation
You can’t manage what you don’t measure. Gather enough samples to trust your numbers and pressure-test the plan without paying tuition to the market.
- Build a 100-trade backtest per setup on recent data; require ≥1.2 expectancy and a max peak-to-trough drawdown ≤10R.
- Walk-forward: 20 sessions of sim/live-micro with identical rules; no parameter tweaks mid-phase.
- Only size up after hitting both: win-rate within ±5% of backtest and drawdown within plan.
- Track distributions: average win, average loss, longest losing streak, and payoff ratio; update monthly.
- If live results deviate >2 standard deviations from the backtest for 30 trades, pause and re-validate assumptions.
Journaling & Metrics That Matter
Journaling isn’t therapy; it’s quality control. Capture the numbers and behaviors that actually move your P&L so you can fix the right problems fast.
- Log per trade: setup name, regime tag, entry/stop/target, R risked, R taken, confluences, time-of-day, news proximity, screenshot.
- Score each trade on execution (0–5): 3 = by the book, 4–5 = clean A-setup, <3 = rule break.
- Weekly review: compute expectancy per setup, equity curve slope, and error cost (PnL lost to rule breaks).
- Kill-switch: if execution score average <3 For a week or 3, rule breaks in a day, drop to sim next session.
- Keep a “couldn’t lose” folder: 20 textbook screenshots per setup to reinforce pattern recognition.
Scaling Capital & Drawdown Protocols
Growth is earned with stability. Increase size only when the system proves it, and cut risk quickly when performance slips to protect longevity.
- Size ladder: after +10R net over any rolling 40-trade window with DD ≤6R, increase risk per trade by 10–20%.
- If drawdown hits 6R from equity high, cut size by 50% and stop new trades after 2 consecutive losing days.
- Recovery mode: requires +4R net and two A-quality sessions to restore full size.
- Monthly hard cap: if down 10R on the month, stop trading and perform a full post-mortem before resuming next month.
Psychology as a System
Mindset follows structure. Make emotions a variable you control by reducing decisions, pre-committing to rules, and shortening feedback loops.
- Trade only during scheduled hours; no “catch-up” sessions after a red day.
- Use pre-commitment: write down your daily loss cap and the exact setups allowed before the open.
- If you feel the urge to “revenge trade,” run a 5-minute timer and re-read your setup rules before any new order.
- Keep a simple breath-reset: 4-4-6 breathing for 60 seconds after a stop-out to prevent tilt.
- End every session with one positive behavior you executed well—reinforce the identity of a rule-follower.
Tools, Charts & Levels
Clarity beats clutter. Use the minimum viable toolkit to define value, momentum, and levels you can trade against without hesitation.
- Chart template: clean candles, 20/50 EMA, VWAP (session), ATR(14), session/previous day high-low, and IB range.
- Only draw levels from daily/4H and the active session; delete stale lines each day.
- Alerts at key levels replace screen-staring; no micro-timeframe entries unless aligned with a higher-timeframe plan.
- News filter: trade only predefined news plays; otherwise, stand aside 2 minutes before and after high-impact releases.
- Slippage check once per week: compare expected vs actual fill; if >0.2R average on market orders, switch to limit or widen stops accordingly.
Size Risk in R, Not Dollars—Keep Losses Boring and Small
Alexander Douedari hammers this point home: think in “R,” the fixed amount you’re willing to lose per trade, not in raw dollars. When you standardize risk, every setup is graded on the same scale, and decision quality is easier to measure. One trade might risk 0.5R to target 2R; another might risk 1R to target 3R—but the language stays consistent. That consistency keeps emotions from hijacking your sizing when a chart “feels” better than your rules say it is.
Working in R also builds durable discipline. You set your stop where the setup breaks, calculate size to equal your predefined R, and then you let the math do the heavy lifting. Green or red, each outcome plots neatly on your expectancy curve, not your ego. Keep R small enough that a losing streak is survivable, and you’ll give your edge time to play out without panic or FOMO.
Trade the Regime: Trend Continue, Range Fade, Transition Stand Aside
Alexander Douedari keeps it simple: your setup only lives where the market supports it. In a clean trend, he looks to join strength on pullbacks to value and lets runners breathe; in a sideways range, he fades failed breaks back toward the middle, where mean reversion does the work. The trick is naming the regime before you trade, not after, so your action follows the environment and not your opinion.
When conditions are shifting—noisy EMAs, choppy structure, mixed signals—he stands aside rather than force a read. That pause protects both capital and confidence, because the plan is built for signal, not noise. Define the regime, match the tactic, and skip the in-between; that’s how you keep execution clean and the edge intact.
Volatility Drives Allocation—Scale Up in Flow, Down in Chop
Alexander Douedari treats volatility like a volume knob for risk. When the tape is moving cleanly and ranges are expanding, he gives winning setups more room and slightly higher size; when volatility compresses and wicks get nasty, he cuts size and shortens targets. The idea is simple: your edge expresses best when markets are paying; when they’re not, you pay less to find out. He watches ATR and the session range to decide whether today deserves full throttle or glide mode.
In practice, Douedari ties risk to objective measures, not vibes. If ATR(14) and realized range sit in the upper band of recent history, he’ll allow runners and pyramid only on planned add-ons; if they’re in the basement, it’s one-and-done with tight risk and faster profit-taking. This keeps the equity curve smoother and the psychology steadier, because allocation flexes with conditions while the rules stay fixed. Volatility doesn’t just change entries—it changes how much you should care; size accordingly.
Mechanics Over Prediction: If/Then Rules Beat Opinions Every Time
Alexander Douedari builds trades like checklists, not forecasts. He starts with a defined condition—if the market is trending and price pulls to value, then prepare. If the trigger fires—break of structure or a specific candle confirmation—then enter with pre-sized risk. If the structure fails, then exit without debate.
The power is in removing wiggle room. Douedari’s workflow forces decisions into yes/no boxes so emotions can’t negotiate mid-trade. If price reaches +1R before a reversal signal, then scale; if volatility compresses, then tighten targets; if two rule breaks happen in a session, then stop trading. Opinions change with every tick, but mechanics don’t—and that’s why the rules win.
Diversify by Setup, Timeframe, and Session—Not Just By Ticker
Alexander Douedari doesn’t spread risk across a dozen symbols—he diversifies how the edge shows up. That means running a continuation and a mean-reversion setup, each validated on two timeframes, and executed during the specific session when they historically pay best. If the London open tends to reward breaks and the New York lunch chops, he shifts tactics instead of forcing one play everywhere. This way, correlation drops because the drivers of PnL are different—mechanics, timing, and structure—not just different tickers that move together anyway.
He also avoids stacking the same exposure in disguise. Taking three “pullback to value” trades across correlated markets is one bet, not three, so he caps concurrent positions by setup, not just instrument. When conditions change, Douedari rotates: fewer trades in the weak session, focus on the setup with the strongest recent expectancy, and keep total open risk within a fixed R limit. The result is smoother equity with fewer “all eggs, one basket” drawdowns—built from variety in method, timeframe, and session rather than a watchlist that only looks diverse.
In the end, Alexander Douedari’s edge isn’t a magic indicator—it’s a rule-based machine: prove a statistical advantage on paper, build around a few repeatable plays, and make sure the plan fits your personality, time window, and market phase so you can execute it the same way tomorrow. He stresses positive expectancy, regime awareness (trend vs. range), and a simple library of entries/exits supported by risk and trade management blocks—the “seven building blocks” that turn theory into consistent live execution.
Douedari’s north star is accountability and math: structure like an institution even if you’re retail, speak in R, cap daily losses, and let numbers—not feelings—dictate sizing and expectations. He’s blunt about avoiding hype cycles and manipulated products unless you specialize in them; the job is to protect capital, not donate it to pump-and-dumps. Build the skill set, value transparency and consistency, and treat psychology as the byproduct of a well-engineered process—not a substitute for it.
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