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In this interview on the Words of Rizdom podcast, the host sits down with development scientist David Opar—sharing a raw, moving story that starts in Nairobi’s Buruburu slums and stretches through boarding school hardships, UK studies, a PhD in South Korea, and a life-threatening health scare. David isn’t a trader, but his arc is exactly what traders study: discipline under pressure, process over hype, and the stubborn refusal to quit when the market (or life) punches hard.
Read on to learn how to convert setbacks into edge—building a routine that survives drawdowns, crafting a risk mindset that resists ego, and developing the “calloused mind” needed to execute your strategy on red days as confidently as on green ones. We’ll pull practical lessons from David’s path—faith, family, fitness, and relentless iteration—and translate them into trade planning, journaling, and risk controls you can apply today.
David Opar Playbook & Strategy: How He Actually Trades
Read This First: Translating High Performance to Markets
David Opar is a world-class sports performance scientist, not a financial trader. This guide translates his high-performance methods—load management, injury prevention, periodization, monitoring—into a practical trading framework you can run today.
- Treat your account like an athlete: protect capacity first, chase gains second.
- Map every rule to a measurable metric (risk %, ATR, win rate, weekly pain).
- If capacity or clarity drops, you de-load risk before you “get hurt” (big loss).
Capacity Management = Position Sizing
In sport, too much load without adaptation causes injury. In trading, too much size without an edge expression causes a drawdown. Manage “load” with strict sizing that scales to volatility and mental freshness.
- Base size = 0.5% risk per trade; max stacked risk across open trades = 1.5%.
- Volatility gate: if ATR(14) / price > 2.0%, cut size by 40%; < 1.0%, allow base size.
- Two losing trades in a day ⇒ 50% size reduction; three ⇒ stop for the session.
- Weekly max loss (“team availability”) = 3R; hit it and you’re benched until next week.
Screening & Prevention: Stop Getting “Injured”
Athletes screen weak links before they break; traders screen weak behaviors before they blow up. Run fast checks pre-market and pre-trade to eliminate preventable damage.
- Pre-market screen: slept ≥ 7h, news map done, bias scored; if any fail, trade half size.
- Pre-trade screen: thesis, level, trigger, stop, target written; no checklist = no entry.
- Mandatory stop placement before entry; hard stop never wider than 1.2× recent swing.
- If you move a stop once, you close the trade—no negotiations mid-rep.
Periodization: Weekly Blocks With Clear Objectives
Pros periodize training blocks; traders periodize execution blocks. Assign each week a focus (trend-following, mean-reversion, or sit tight) based on regime, then grade it.
- Sunday: define regime (trend/neutral/rotate) from higher-timeframe structure.
- Pick one primary setup for the week and one backup—no menu of five.
- Daily plan: 2 sessions × 90 minutes of peak focus; no more than 6 planned trades/day.
- Friday: grade A/B/C; A = scale rules next week, C = de-load risk by 50%.
Warm-Up & Cool-Down: Routines That Reduce Errors
Warm-ups reduce injury risk; pre-market routines reduce dumb trades. Cool-downs harvest learning while emotions cool.
- 10-minute warm-up: mark levels, replay last session’s top setup, write first trigger.
- First 15 minutes after major data = observe only; trading starts after one full candle close.
- Cool-down: screenshot best/worst trade, tag rule adherence (✓/✗), note fix for tomorrow.
- End-of-week: top 3 charts + 1 page of notes; archive to a living playbook.
Objective Monitoring: Dashboards > Feelings
Athletes use force plates; traders use dashboards. Your data tells you when to push or pull back—feelings don’t.
- Track: R per day, win rate, average adverse excursion (AAE), average favorable excursion (AFE).
- If AAE > 0.75×, stop on average, tighten entry, or trade fewer breakouts.
- If AFE < 1R for 5 sessions, market not paying—switch to mean-revert or sit out.
- Green-light day only if: last 20 trades ≥ 52% win OR EV ≥ +0.2R; else yellow light (half size).
Return-to-Play After Drawdown
Injured athletes follow protocols back to the field. After a losing streak, you earn your size back with proof, not hope.
- −5R from equity high ⇒ de-load to 0.25% risk; −8R ⇒ stop trading for 48 hours.
- To re-scale: need 10 consecutive checklist-compliant trades and +3R net to regain base size.
- During RTP, only take A-setups at A-levels; one B-setup = session ends.
- Daily cap during RTP: 2 trades; hit daily −1.5R and you’re out for the day.
Edge Construction: Simple, Testable Setups
Opar’s work prizes clarity and repeatability. Your playbook should too—define setups in one sentence and test them.
- Trend pullback long: HTF uptrend, price reclaims session VWAP, 15m higher low; stop below swing; target 1.5R first, trail under 15m swing.
- Range fade: HTF neutral, 3 touches establish range; fade at extremes only with reversal candle close; stop 0.8× ATR beyond level, target mid-range.
- Post-data continuation: strong catalyst aligns with HTF bias; enter on first pullback that holds VWAP; if pullback violates VWAP, stand down.
- One filter per setup: e.g., RSI divergence or market breadth confirmation—never stack five.
Recovery & Availability: Protect the “Athlete”
You can’t execute if you’re exhausted. Availability beats intensity. Build recovery into the calendar and enforce it like a stop.
- Hard stop trading 30 minutes before your usual fatigue window.
- One full no-screens day per week; two per month after heavy news clusters.
- If HRV/energy proxy is poor (or you feel foggy), trade only planning, not execution.
- No revenge sessions after social conflicts, travel, or illness—your risk is impaired.
Coaching Loop: Feedback That Actually Changes Behavior
Elite teams close the loop fast. You’ll get better when your feedback is immediate, specific, and tied to rules.
- Tag every trade with setup name, rule compliance (0–3), and emotional state (0–2).
- Weekly, delete any setup with < +0.1R EV over 40 trades or < 40% win with 1.5R target.
- Promote any setup with > +0.25R EV and clean execution to “priority” next week.
- One improvement target per week (e.g., “no impulsive entries”); measure it, score it.
Risk Architecture: Fail-Safes for Worst Days
When things go wrong in sport, equipment and protocols limit damage. Your trading needs fail-safes that trigger automatically.
- Platform-level daily loss limit = 1.5R; platform auto-locks on breach.
- Broker OCO orders: entry auto-attaches stop and target; no naked orders.
- Position correlation cap: no more than 2 positions in the same factor bucket (e.g., USD-long).
- News firewall: 10 minutes pre/post Tier-1 releases = flat unless pre-planned.
Culture & Environment: Make Good Decisions Easy
High-performance environments make the right choice the default. Shape your desk, tools, and team to reduce friction.
- Keep only the charts and signals that directly feed your setups; remove the rest.
- Use a visible checklist beside the screen; every box must be ticked before clicking buy/sell.
- Share weekly grades with an accountability partner; must explain any rule breach in writing.
- Maintain a “do-not-trade” list (assets/time windows) where your stats are negative.
Scaling & Peaking: When to Push
Athletes taper and peak for big events; traders scale when edge and conditions align. Push only with proof.
- Three A-setups hit in a week and EV > +0.3R over the last 30 trades ⇒ increase size by 20% next week.
- During earnings/CPI/NFP weeks, either pre-plan specific plays or default to half size.
- If slippage exceeds 0.3R on two trades in a session, stop market orders—use limit or skip.
- Never widen stops to “stay in”—reduce the size so the stop can stay where it belongs.
Skill Practice: Reps Without Cost
Athletes rehearse. Traders can too. Build low-stakes reps that strengthen recognition and execution.
- Daily 15-minute replay: scroll through yesterday’s session and mark the first valid trigger you missed.
- One paper-trade session per week, focusing on entries only; grade timing vs. plan.
- Micro-challenge: 10 trades with perfect stop discipline; any breach resets the counter.
- Quarterly: backtest your top setup on a fresh 12-month slice to check drift.
Size Risk Like a Pro: Fixed R, Never Martingale Into Pain
David Opar’s play here is simple: decide your R before the trade and defend it like your edge depends on it—because it does. Pick a fixed percentage of equity per idea (for example, 0.25–0.5% risk per trade) and let that dictate position size, not your feelings about the setup. When the stop is hit, you’re out—no re-centering, no “just a little wider,” no chasing the loss with a bigger size. This is how you turn randomness into a controlled game and keep your head clear for the next opportunity.
Opar also leans hard against all forms of martingale thinking. If a trade is invalid, he closes it and resets rather than “averaging for comfort” while the thesis dies. Winners can be scaled only after a partial take or a structural confirmation, never because you’re “due.” The scoreboard is R-multiples over a series, not the outcome of one hero click. Keep the unit of risk fixed, keep the stop honest, and the distribution will do the heavy lifting over time.
Let Volatility Set Your Size: ATR Gates, Wider Stops, Smaller Bets
David Opar treats volatility like the field conditions—if it’s choppy or fast, he adjusts the game plan. He uses ATR gates to decide whether he earns the right to take a normal size: below a threshold, base risk; above it, cut size, and widen the stop so the trade can breathe. No fixed-pip stops or “one-size-fits-all” entries—risk is calibrated to the instrument’s current pace, not yesterday’s comfort zone. When ATR expands, David reduces position size proportionally so the dollar risk per trade stays constant even as stops widen.
He also sets a daily volatility governor: if spread/ATR slippage exceeds a predefined fraction of R, he stands down or switches to limit-only entries. Scaling occurs only after the first partial has locked in R, never during the initial volatility burst. If the 15m ATR spikes post-news, he waits for one full candle close to verify that the move isn’t just noise before committing fresh risk. By letting volatility dictate both stop distance and size, David Opar preserves an edge on wild days and keeps his equity curve smoother when most traders get chopped to pieces.
Diversify By Strategy, Underlying, and Timeframe—Not Just Tickers
David Opar points out that holding five tech names isn’t diversification; it’s one crowded theme split five ways. Real resilience comes from mixing trade types (trend, mean-reversion, breakout), different underlyings (FX majors, indices, commodities), and varied holding periods. When one regime punishes breakouts, mean-reversion can still pay the bills. He maps each position to a dominant factor—rates, dollar, growth, energy—so he knows when positions secretly rhyme. If two trades respond to the same factor, he treats them as one and halves the combined risk.
He also staggers durations to smooth equity swings: intraday for cash flow, swing for core trend, and occasional position trades when macro lines up. Each bucket has its own rules, targets, and review cadence so losses don’t cluster from identical mistakes. During hot streaks in one bucket, he caps exposure and seeds another to avoid overfitting to recent conditions. David Opar keeps a rolling correlation check on his book and cuts overlap before the market does it for him.
Trade Mechanics Over Predictions: Triggers, Checklists, Post-Entry Management Rules
David Opar doesn’t try to be a fortune teller—he’s a mechanic. Before any click, he wants one clean trigger that’s objective and visible: reclaim of VWAP after a higher low, break-and-retest of a daily level, or a volatility contraction releasing into trend. He confirms the trigger with a short checklist—trend context, location, risk distance, news window—because one miss on the checklist usually becomes a bigger miss on P&L. If a box isn’t ticked, David stands down; the next candle can always be the trade, but a broken process becomes a broken account.
Once in, he shifts from prediction to management. First partial comes at 1R–1.2R to pay for information; stop goes to break-even only after structure confirms, not merely because price moved a bit. If momentum stalls or VWAP flips against him, he cuts and re-qualifies rather than “hoping” the thesis returns. Add-ons are earned on fresh signals at the new structure—not because he “feels” stronger—so each unit can survive on its own merits. That’s David Opar’s edge: the rules decide the trade, and the trade never gets to rewrite the rules.
Define Risk Before Click: Daily Loss Caps, OCO, News Firewalls
Before a single order goes live, David Opar decides the maximum damage the day is allowed to do—then he hardwires it. He uses a fixed daily loss cap in R and a platform lockout, so discipline isn’t optional when emotions spike. Every entry is paired with OCO orders—stop and target attached—so there’s never a naked position “just for a second.” He sets a news firewall for Tier-1 releases: flat 10 minutes before and after, unless a pre-planned playbook exists. If a trade triggers inside the firewall by mistake, he flattens immediately and logs it as a rules breach.
David also caps correlation and concurrency so risk can’t silently stack. No more than two positions in the same factor bucket, and no more than three open trades total when volatility is elevated. If slippage or spread consumes more than a set fraction of R, he switches to limit-only or stands aside for the session. Break-even moves and time stops are rules-based: stop to BE only after structure confirms; exit on a timed fail, not a hope. That’s how Opar keeps the account eligible to fight tomorrow—risk defined first, execution second, opinions last.
In the end, David Opar’s message lands like a blueprint for durable performance: protect capacity first, then let repeatable rules do the compounding. He shows how fixed-risk units, volatility-aware sizing, and tight execution checklists turn uncertainty into a game of controlled probabilities. When conditions change—news shock, regime shift, or just a foggy day—he de-loads, resets, and earns size back with proof, not hope. That simple bias toward process over prediction is what keeps the account eligible for tomorrow.
Just as athletes use periodization, screening, and recovery to avoid injury, David’s approach translates into weekly focus blocks, pre-trade gates, and hardwired fail-safes like daily loss caps and OCO orders. Diversifying by strategy, underlying, and timeframe reduces correlation risk, while post-trade reviews and objective dashboards close the feedback loop fast. The core takeaway is deceptively simple: write the rules, measure the rules, live by the rules—because your edge isn’t what you believe about the market, it’s what you repeatedly execute when it counts.
