Table of Contents
This episode features Tarik, the CEO of Capital.com, opening the curtain on retail trading at real scale—think millions of clients and staggering monthly volumes—plus a candid take on brokers, prop firms, and what separates flash-in-the-pan wins from sustainable performance. Filmed with a “no fluff” vibe, Tarik explains how regulation, execution speed, and risk offloading work behind the scenes, and why reputable brokers want traders to survive for years, not weeks. You’ll also hear why his team doubled down on social media to reach serious traders who never click ads, and how that content-first approach brought in high-intent clients.
What you’ll learn here is intentionally beginner-friendly: how to pick a broker (regulation and banking matter), why “zero spread” often hides slippage, and how tools like guaranteed stop-losses are basically cheap insurance. Most importantly, Tarik shows that wins come from psychology first—controlling greed, revenge trades, and fear—then pairing that mindset with a simple, written plan and post-trade reviews. You’ll leave with a clearer path: choose markets you understand, keep setups simple, pre-commit your risk and targets, and stop tinkering mid-trade.
Tarik Playbook & Strategy: How He Actually Trades
Core Thesis & Edge
Here’s the big idea Tarik runs with: survive first, compound second. He treats trading like an operating business—defined costs, repeatable processes, and zero tolerance for “winging it.” The edge is built from clean execution, simple setups, and strict rules that cut off downside before hunting upside.
- Define your edge in one sentence (e.g., “trend pullbacks into value with momentum confirmation”).
- If you can’t describe the setup rule-by-rule, you don’t have it; don’t trade it.
- Track win rate, average win, average loss, and payoff ratio weekly—optimize the system, not single trades.
- The first KPI is account survival: max daily drawdown ≤ 2%, max weekly drawdown ≤ 5%.
Markets & Timeframes
He focuses on liquid markets where spreads and slippage stay tight at most times of day. Timeframes are chosen to reduce noise but still generate enough signals to matter. You want a “boring repeatable window,” not constant FOMO.
- Trade 1–3 instruments you understand deeply (e.g., major FX pairs, top indices, gold).
- Primary timeframe for bias: H4; execution: M15–M30; optional: H1 for context and D1 for regime.
- Avoid the first 5 minutes of major data releases; execute after the spread normalizes.
- If spread > average by 50% or book looks thin, skip the signal—no “liquidity tax.”
Setup: Trend-Pullback (Primary)
The bread-and-butter is catching continuation after a shallow pullback into value. You’re aligning higher-timeframe momentum with a clean intraday entry trigger. Simple ingredients, consistent rules.
- Bias long only if H4 is above its 50-period MA and making higher swing lows (reverse for shorts).
- Mark the value area with a 20/50 moving-average zone or anchored VWAP from the most recent H4 impulse.
- Wait for price to pull back into value and print a bullish rejection (wick > body, closes above value).
- Confirm with RSI crossing back above 50 or MFI uptick; if both disagree, pass.
- Place a stop below the pullback low; entry on the next candle’s break of rejection high.
- First target = 1R; move stop to breakeven at +0.8R; scale 50% at 1.5R; trail remainder under M15 swing lows.
Setup: Mean-Reversion (Secondary, Only in Ranges)
When a higher-timeframe trend is flat and price oscillates, he switches to a defined-risk mean-reversion play. The key is strict range identification and faster exits—no “let it ride” mentality here.
- Trade mean-reversion only if D1 ATR is falling and H4 swings are overlapping (no clear HH/HL or LL/LH).
- Define range with two clean H4 reaction levels touched ≥3 times.
- Enter fade only with an exhaustion signal (divergence on RSI/MFI and a long-wick rejection).
- Stop goes beyond the range extreme; target mid-range first, far side second, only if momentum flips.
- If price closes outside the range on H1, exit—no “hope” allowed.
Risk Sizing & Daily Guardrails
He sizes positions so single trade outcomes never threaten the plan. Daily and weekly guardrails prevent tilt, revenge, and sloppy execution after losses or big wins.
- Risk per trade: 0.25%–0.5% account; cap concurrent risk at 1%.
- Max 3 trades per session; stop trading for the day after 1.5R or +3R, whichever comes first.
- For scheduled high-impact news, halve size or stand down completely 15 minutes before/after.
- Slippage buffer: assume 0.1R slippage on indices/metals; if realized slippage >0.2R twice, cut size.
Entries, Orders & Execution Hygiene
Execution is where many edges die. Tarik standardizes orders and tolerances so that fills and behavior are consistent. The aim: make each click look the same.
- Default to stop orders at the trigger; avoid market orders unless re-entering after platform hiccups.
- Hard stops are always on the server; never mental stops.
- If the spread widens during the entry candle, wait one bar—no chasing.
- If your stop would sit inside the average spread ×2, skip the trade (structurally fragile stop).
Trade Management Rules
Once in, you manage risk first and profits second. Pre-committed actions remove in-the-moment bias and keep statistics stable over time.
- Move to breakeven at +0.8R; never earlier.
- If price stalls for 5 bars without hitting +0.5R, reduce position by 25% and keep original stop.
- Trail only after partial at 1.5R; use last confirmed M15 swing or 20-EMA close, whichever is tighter.
- If opposing H4 signal prints, flatten remainder—don’t fight regime shifts.
Psychology & Session Discipline
He treats psychology as a checklist, not a vibe. You’re either fit to execute or you’re flat. A few objective gates keep you from trading your mood.
- Pre-session check: slept ≥6h, no alcohol last 24h, no unresolved stress events—fail any, stand down.
- 2-minute breathing before first trade; post-loss reset walk (3 minutes) before re-entry.
- No P&L on screen; show only R-multiple and position size.
- If two consecutive process violations occur, end the session and write a corrective plan before the next open.
Broker & Execution Controls
Because he’s run a brokerage, he’s ruthless about execution quality. You can’t control the market, but you can control your plumbing. Small frictions compound just like returns.
- Use a regulated broker with segregated client funds; verify negative-balance protection is active.
- Enable guaranteed stop-loss where available on volatile instruments; price it as insurance, not edge.
- Compare effective cost monthly: spread + commission + average slippage in R (target <0.25R/trade).
- If platform latency >150ms during your session hours, change server or switch account.
Playbook Automation & Journaling
Your playbook isn’t real until it’s measurable. He automates the boring bits, then reviews like a coach. That’s how the edge gets sharper without adding risk.
- Journal every trade with 3 screenshots: HTF bias, entry trigger, exit rationale.
- Tag trades by setup (trend-pullback, mean-reversion), market condition (trend/range), and news proximity.
- Weekly: cut bottom-quartile tags by size 50% or remove them if payoff <1.1.
- Maintain a “Do More / Do Less” page; only change one variable per week (size, filter, or target).
Data Windows & Improvement Loops
Progress happens in defined sprints, not random tweaks. He runs fixed windows to evaluate the system under consistent conditions, then scales what works.
- Optimize on the last 90 trading days; validate on the prior 90—no cherry-picking.
- Require ≥30 trades per setup before judging; if signal count is too low, widen markets, not rules.
- Scale risk by 10–20% only after two consecutive green weeks with full rule compliance.
- If weekly expectancy <0.2R for two weeks, pause live trading and simulate>0.3R.
Size Risk First: Let Position Sizing Dictate Every Trade Decision
Tarik hammers this home: before you think entries, you set risk. He treats position size as the steering wheel, not the seatbelt—control it and the rest of the car behaves. Define the dollar risk first, then let the stop distance and volatility calculate units, not your feelings. When markets speed up, your size dials down automatically; when they calm, size can step back up.
He keeps risk per trade small—think fractions of a percent—so a string of losers can’t sink the week. Daily and weekly loss caps shut the platform before emotion starts negotiating. The plan is simple: size by ATR or stop distance, round down, and refuse any trade that requires “just a bit more” size to look good. In Tarik’s words, your edge lives or dies at the position-sizing screen, long before you ever click buy.
Trade Volatility, Not Price: Allocate by ATR and Regime Shifts
Tarik’s view is simple: price lies, volatility tells the truth. He builds allocation around how fast the tape is moving, not where it’s going. Using ATR and recent range expansion, he decides whether to throttle risk down or allow normal size. When ATR spikes or a regime flips from quiet to wild, Tarik cuts size, widens stops proportionally, and demands cleaner signals before engaging.
In calmer regimes, Tarik lets the system breathe—normal size, standard targets, and no heroics. He checks for regime changes around scheduled catalysts and the first hour after major opens, treating those windows as separate “weather systems.” If realized volatility exceeds the backtest assumptions by a set threshold, he stands down until it normalizes. For Tarik, trading volatility means adapting your risk engine first; the entry is just the last step.
Diversify By Underlying, Strategy, and Duration To Smooth Equity Curve
Tarik’s playbook avoids single-point failure by spreading bets across what moves, how you trade it, and how long you hold it. He mixes uncorrelated underlyings—majors, an index, maybe gold—so one market’s mood swing doesn’t hijack the whole account. Then he layers strategies: a trend-pullback engine for momentum days, a tight mean-reversion for clean ranges, and a news-avoidance filter to keep those lanes from colliding.
Duration is the third leg of Tarik’s stool—intraday executions for cash flow, swing holds for the bigger waves, each with separate risk caps. He tags trades by asset, setup, and hold time, then trims whatever cluster is dragging expectancy. If two lanes start correlating (same drawdown curve, same timing), he cuts the size on one until the lines decouple. In Tarik’s words, a smooth equity curve isn’t luck; it’s engineered by separating your risks before the market tries to bundle them.
Choose Defined Risk Over Undefined: Pre-Plan Stops, Targets, and Exits
Tarik won’t touch a setup unless the worst-case loss is fixed before entry. He writes stops into the order ticket, not into his head, then sizes the position off that distance so the dollar risk is constant. Targets are pre-chosen in R-multiples, and he only trails after the first partial hits—never sooner. If spread flares or slippage would shove the stop inside the noise, Tarik passes and waits for a cleaner window.
He also scripts exits for when the trade underperforms: time stops if momentum dies, structure breaks if the higher-timeframe flips, and full flattening if an opposing signal prints. No averaging down, no widening stops, and no “it’ll come back.” Tarik treats undefined risk as a business killer; defined risk is the insurance policy that keeps you solvent long enough for the edge to play out. The discipline is simple: plan the loss, earn the win, and execute exactly what the plan says.
Mechanics Beat Predictions: Systematic Entries, Checklists, Relentless Process Discipline
Tarik makes it boring on purpose—because boring prints P&L. He follows a pre-trade checklist that forces alignment across timeframe bias, location, trigger, and risk, so the entry is just a mechanical yes/no. If any checkbox fails—spread too wide, news window too close, signal not clean—he doesn’t negotiate with himself; he skips. Tarik’s mantra is that opinions are entertainment, but mechanics are execution.
Once in a trade, Tarik executes the same sequence every time: move to breakeven at the predefined milestone, partial at the first target, and trail only after momentum confirms. He documents the outcome with screenshots and notes the exact rule that justified each action, then scores himself on process, not P&L. If he breaks a rule, the next session starts with reduced size until he strings together clean reps. In Tarik’s world, prediction is optional—but the checklist is mandatory.
In the end, Tarik’s message is brutally practical: survival comes from defined risk, not clever predictions. He frames stop-losses as non-negotiable seatbelts, points to real shock events (Brexit, negative oil) to show how fast “great” trades can flip, and treats guaranteed stop-losses like insurance you’re glad you bought only when the crash happens. The takeaway is simple: pre-plan loss, size by volatility, and you’ll still be in the game when opportunity returns.
He’s equally blunt about execution plumbing and broker choice. Ignore “zero spread” marketing if it hides worse fills; pay attention to effective cost—spread, commission, slippage—and stick with regulated shops where your money and fills are treated like they matter. Tarik’s brokerage lens is crystal clear here: cheap on paper but slippery in practice is the most expensive path a trader can choose.
Finally, the edge is process: write down why you’re taking the trade, review it afterward, and get better on purpose. Tarik pushes reflection like an athlete studying film—sleep, routine, post-mortem, repeat—and he’s unapologetic about using modern channels to teach those basics at scale. If you want longevity, adopt the habits: checklist before entry, journal after exit, iterate weekly. That’s how a retail trader becomes durable.
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