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This interview sits down with Kevin McCormick—2021 Robbins Cup Futures World Champion with a 253.8% return—on the Words of Rizdom podcast in Phoenix. McCormick, who studied under Larry Williams, explains why retail traders can be more nimble than billion-dollar funds and how long-term narratives (like inflation or tech cycles) anchor his execution. You’ll hear candid stories about media “propaganda,” the importance of a trading journal, and why liquidity and rule-following beat hot takes.
In this piece, you’ll learn McCormick’s beginner-friendly blueprint: identify the big trend first, then trade around it; focus on liquid markets; size for inevitable losing streaks; and avoid chasing day-trade hype if it conflicts with real life or risk limits. We’ll also unpack how journaling fixes false positive reinforcement, why retail data access is a real edge, and how to think about multi-year themes like AI infrastructure while still managing near-term swings.
Kevin McCormick Playbook & Strategy: How He Actually Trades
Core Philosophy: Trade the Big Narrative, Not Every Wiggle
Kevin McCormick frames markets through multi-month narratives—like inflation cycles or technology build-outs—and then trades around that backbone. This keeps him aligned with the dominant flow while avoiding the churn of constant prediction on noise.
- Define the 6–24 month “primary narrative” (e.g., inflation upcycle, AI infrastructure, housing softness) before placing any trade.
- Only take trades that express or hedge that narrative; skip everything else.
- Re-validate the narrative weekly: “What changed?” If nothing material has changed, keep the plan unchanged.
- Keep a one-page narrative sheet: drivers, key data points to watch, and markets that best express it.
What to Trade: Liquidity First
He prioritizes liquid futures and ETFs where slippage is small and exits are reliable. Liquidity also helps you size up when right and cut quickly when wrong.
- Prefer contracts with tight spreads and deep books (index futures, major commodities, rates).
- Avoid thin markets unless there’s a clear structural edge and you’ve tested fills across regimes.
- Set a maximum slippage per trade (e.g., 0.5–1 tick on index futures, 1–2 ticks on liquid commodities). If the book can’t support it, don’t trade.
- Pre-define an “emergency exit” mechanism (market order at X time/level) for platform or liquidity surprises.
Timeframe & Pace: Swing the Trend, Trade Around It
He’s not chasing every intraday pop. The edge is calmer: anchor to higher-timeframe direction, then work entries around pullbacks, volatility compressions, and event dislocations.
- Choose a base timeframe for bias (daily/weekly) and an execution timeframe (60–240m).
- Only look for longs in an up-bias regime and shorts in a down-bias regime; neutrality means smaller size and faster exits.
- Map “add zones” before the week starts (prior value area highs/lows, moving VWAP bands, weekly highs/lows).
- If you take three trades against the dominant trend in a week, stop and reassess the narrative.
SSet upFilter: Fundamentals + Tape Agreement
He wants fundamentals and tape to rhyme. Narrative gives the “why”; price action confirms the “when.”
- Require two confirmations: (1) narrative driver intact, (2) price acceptance above/below a key level on your execution timeframe.
- Define a “no-trade zone” around major prints (FOMC, CPI, jobs) unless your plan explicitly includes event risk.
- If price rejects your key level twice, downgrade the setup quality and reduce the size by 50% until acceptance returns.
- For commodities, tie setups to inventory/seasonality calendars and major macro prints that impact demand/supply.
Risk & Sizing: Built for Losing Streaks
He sizes so that normal variance—strings of losers—doesn’t force him out of the game. Respecting risk keeps him available for the fat-tail winners that make the year.
- Hard-cap per-trade risk at a small fraction of equity (e.g., 0.25–0.75%); scale with liquidity and confidence.
- Pre-compute a 5- to 8-trade losing-streak tolerance; if a planned size would violate it, cut the size.
- Use structure-based stops (prior swing/invalid level) plus a time stop if the thesis stalls.
- Auto-de-lever after a −3R to −5R day or −6R week; claw back with half-size until back above the drawdown trigger.
Position Management: Add on Valid, Not on Hope
Winning trades can be pressed—if the market proves your thesis at the next decision point. Adds are earned, not assumed.
- Only add when price accepts above/below your next pre-defined level with volume/time spent, not just a wick.
- Move the stop on the whole position to the prior add’s invalidation after each add.
- Partial-out into obvious targets (prior high/low, measured move) but keep a runner if the weekly trend is intact.
- If you add and price immediately re-enters your prior value area, remove the add and revert to core size.
Journal & Review: Kill Bad Reinforcement
He’s militant about journaling to avoid “getting paid for the wrong behavior.” The journal aligns the process with P&L.
- For every trade, log: narrative statement, setup tag, entry/exit rationale, stop, add/scale rules, and post-trade emotion.
- Tag outcomes by process quality (A/B/C), separate from P&L; a profitable C-trade is still a mistake.
- Weekly: export tags to find your best pairings (e.g., “inflation + energy pullback” vs. “range-breaks post-FOMC”).
- When you spot a repeated process error (e.g., FOMO adds), write a one-sentence “If-Then” rule and pin it to your screen.
Data Edge: Filter the Noise, Track the Signal
He treats media narratives skeptically and focuses on data that actually moves his markets. The edge is speed and clarity, not headlines.
- Maintain a short “must-watch” list per narrative: primary indicator, secondary, and a tie-breaker.
- Pre-write how each print alters your plan (e.g., “If CPI core > X, keep long energy bias and avoid fades for 48h”).
- When major data contradicts your bias twice in a row, downgrade the narrative and cut size untilrealignmentt.
- Ignore opinion pieces; act on numbers and price response.
Event Playbook: Plan the Volatility
Catalysts can hand you location—if you’re prepared. He treats events like scheduled hunting windows.
- Build a week-ahead calendar: prints, earnings clusters (for equity index), OPEC/DOE for energy, USDA for ags, FOMC for rates.
- Define pre-event positioning rules (flat/reduced/hedged) and post-event triggers (acceptance/failed move).
- First 15–30 minutes post-print: observe response, not opinion. Only engage on acceptance beyond your level.
- For outsized gaps, use “first pullback to decision level” rather than chasing the initial spike.
Markets & Expressions: Futures-First, ETFs for Simplicity
He frequently uses futures for precision and capital efficiency, and keeps ETF equivalents as a simplified expression when appropriate.
- Map your narrative to its cleanest tickers (e.g., ES/NQ for growth cycles, CL/HO/RB for energy-inflation, ZN/UB for rates).
- Keep an ETF/CFD mirror list for swing accounts and to test correlations.
- If correlation breaks across your basket, assume “regime wobble” and reduce cross-position risk.
- Use spreads (e.g., calendar or inter-market) when they better isolate the narrative driver.
Lifestyle Fit: Sustainable Over Sexy
He avoids forcing day trading if it clashes with real-life rhythm. Consistency beats screen-glued heroics.
- Choose a trade frequency you can sustain for a year (e.g., 2–6 quality executions per week).
- Set daily “no trade windows” tied to your schedule; protect them like risk limits.
- If you miss a move, log it and plan the next valid entry; never “recreate” the missed R with an impulse trade.
- Tie compounding goals to process metrics (A-grade trades taken) rather than an arbitrary daily P&L.
Year Construction: Let the Fat Tail Pay You
His standout year came from aligning with a dominant macro theme and letting a handful of trades do the heavy lifting.
- Start each quarter with three “Core Themes” and two “Wildcards,” ranked by conviction.
- Expect that 20–30% of your trades generate 80% of P&L; structure size and patience around them.
- After a large winner, pre-commit to a cool-down rule (e.g., 24–48h no new risk) to avoid victory laps.
- End of the month: promote/demote themes based on data/price, not hope, and rotate risk accordingly.
Personal Scorecard: Keep It Simple, Make It Repeatable
He distills everything to a repeatable checklist so decisions are fast and consistent.
- Pre-trade: (1) Narrative aligned? (2) Level defined? (3) Liquidity sufficient? (4) Risk < cap? (5) Event risk known?
- In-trade: (1) Acceptance at add level? (2) Stop intact? (3) Emotion < 6/10? If not, reduce risk.
- Post-trade: (1) Tag A/B/C, (2) Note reinforcement quality, (3) Capture one improvement for next time.
- Weekly: update the one-page narrative sheet and archive last week’s so evolution is visible.
Size Risk First: Let Volatility Dictate Position, Not Ego
Kevin McCormick starts with risk, not the chart pattern. He sizes each position by how wild the market is right now, not how confident he feels. If daily swings are big, he dials down size; if they’re tight, he can lean in a bit more. The goal is simple: survive the chop so the strategy can work over many trades.
Kevin ties size to the recent range and where the invalidation lives. He decides the stop first, converts that distance into a small percent of equity, and only then computes contracts or shares. When volatility jumps, he’ll cut exposure automatically rather than “toughing it out.” By letting the tape’s movement set his size, Kevin McCormick keeps drawdowns controlled and gives himself room to catch the next clean trend.
Diversify by Market, Strategy, and Timeframe to Smooth Drawdowns
Kevin McCormick doesn’t bet the farm on one idea or one market. He spreads risk across uncorrelated underlyings—index futures, energy, rates—so one theme wobbling doesn’t sink the week. Then he adds a second layer: multiple strategies, like trend continuation and mean-reversion around key levels, so he isn’t hostage to one market condition. Finally, he staggers timeframes, holding a swing core while tactically trading around it, which helps him harvest R without abandoning the bigger move.
Kevin keeps each sleeve small enough that any single failure is annoying, not fatal. If correlations spike, he cuts overlapping exposure and keeps the cleanest expression of his core narrative. He also rotates risk toward the strategies that are currently paying and away from those out of sync, without breaking his overall risk cap. That way, Kevin McCormick smooths the equity curve and stays funded for the trades that actually make the year.
Trade Mechanics Over Predictions: Rules, Checklists, and Repeatable Execution
Kevin McCormick treats predictions as noise and mechanics as the job. He runs every trade through a short checklist: bias from higher timeframe, level defined, risk sized, and catalyst known. If any box is blank, he passes—no exceptions. Execution is standardized, so entries, adds, and exits look the same across weeks, which keeps emotion out of the driver’s seat.
When the plan says “no-trade,” Kevin respects it even if the tape teases. He grades each trade by process quality, not just P&L, so lucky wins from bad behavior don’t infect the playbook. Post-trade, he writes one concrete fix and updates the checklist if needed. That’s how Kevin McCormick compounds discipline—by making rules the edge and letting predictions sit on the bench.
Prefer Defined Risk Setups; Hedge or Avoid Undefined Tail Exposure
Kevin McCormick builds most trades so the maximum loss is known up front. If a setup requires “praying the market behaves,” he sizes down or skips it entirely. He’ll define risk with structure-based stops, options collars, or spread constructions that cap worst-case outcomes. The objective is durability: live to press the clean opportunities instead of donating to tail events.
When exposure is inherently open-ended—think surprise gaps, commodity shocks, or policy landmines—Kevin either hedges or refuses the ticket. He tracks catalysts and trims size into binary events unless he has a pre-planned hedge that survives a gap. Adds are only permitted if the invalidation level stays intact and the overall portfolio VaR remains inside its limit. By defaulting to defined risk and treating undefined tails as paid risks—not wishes—Kevin McCormick keeps compounding intact.
Build Event Playbooks: Volatility Calendars, Accept/Reject Levels, Post-Print Actions
Kevin McCormick treats big catalysts like scheduled hunting trips, not surprises. He builds a weekly event calendar—CPI, FOMC, jobs, inventories—and decides in advance whether to be flat, hedged, or lightly positioned into the print. For each event, he marks a primary decision level and a backup “line in the sand,” so there’s no guessing when volatility hits. The goal is simple: respond to the market’s reaction, not your opinion about the number.
Right after a release, Kevin waits for acceptance or rejection beyond those levels before committing size. If price spikes then snaps back inside the range, he fades with tight risk; if it accepts outside and holds, he trades in the direction of the break with staged adds. He writes post-print rules—time windows to wait, position caps, and profit-taking triggers—to prevent impulse trades. By turning chaos into a checklist, Kevin McCormick converts volatility into a structured opportunity instead of random stress.
In the end, Kevin McCormick’s edge isn’t a magic indicator—it’s a durable operating system. He anchors every decision to a clear macro narrative, funnels that view into liquid markets, and lets volatility—not confidence—set position size. Defined risk is the default; event risk is planned, and mechanics outrank opinions. That combination allowed him to be both patient with the big swing and opportunistic around it, without letting one hot take or headline derail the plan.
For traders, the playbook is refreshingly repeatable: write the thesis in plain English, trade only the markets that cleanly express it, and cap downside before pressing upside. Keep a tight weekly calendar of catalysts, wait for acceptance beyond your levels, and add only when the market earns it. Journal every trade to kill bad reinforcement and rotate risk toward what’s actually paying, not what you hope will pay. Do this with McCormick’s discipline and you’ll survive the variance, stick around for the fat-tail winners, and build a curve that’s driven by process—not luck.
