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Dr. Brett Steenbarger—trader coach, psychologist, and author—joins us to unpack the real wiring behind consistent performance. From his decades working with hedge funds, prop firms, and independent traders, Brett explains why trading is a performance discipline first and a money game second. You’ll hear how he blends clinical psychology with markets, why paper trading is useful early on, and how pros think in percentages so they can scale smoothly without losing their edge.
In this piece, you’ll learn the trader strategy moves Brett sees work in the wild: start small and “stairstep” size only after you’re profitable across different markets, treat losses as data, and build a repeatable process even if you trade discretionarily. We’ll cover his “positive trading psychology” approach—identify your natural strengths, convert them into skills with mentorship and reps, then protect your mindset with sane risk and a life bigger than P&L—so you can grow like a pro without burning out.
Brett Steenbarger Playbook & Strategy: How He Actually Trades
Core Philosophy: Performance First, Profits Follow
Brett Steenbarger treats trading as a performance discipline, like athletics or music. The goal is to build repeatable skills around a clearly defined edge, then express that edge with disciplined risk and constant feedback. This section lays out the foundation you’ll use to make your rules bite.
- Define “edge” as a specific pattern + context combo that produces positive expectancy in your stats over 50–100 samples.
- Track expectancy explicitly: Expectancy = (Win% × Avg Win) − (Loss% × Avg Loss). Only scale edges with positive expectancy over the last 3 rolling months.
- Separate process goals from outcome goals: 100% adherence to setup criteria and risk rules is the daily scoreboard; P&L is the monthly report card.
- Keep a “playbook” of 3–5 A-setups; archive anything that lacks conviction, clarity, or stats.
- Trade your strengths: if you read order flow well, bias to intraday execution; if you excel at macro/context, bias to swings. Don’t force styles that fight your temperament.
Finding and Framing the Setup
Brett emphasizes that high-quality trades share a common structure: a catalyst, confirmatory market behavior, and clean risk. Here’s how to frame those pieces so your entries stop feeling random.
- Write a one-sentence thesis before entry: “IF [context] AND [pattern] THEN risk to [invalid level] for [target path].”
- Require a catalyst: session imbalance, economic release reaction, opening drive failure, or multi-day value migration. No catalyst = no trade.
- Demand confirmation: e.g., higher low after a failed breakdown on rising volume; or delta divergence into prior day value.
- Mark invalidation precisely (the level that disproves your thesis), not a “comfortable” stop.
- Enforce location: only take longs near prior demand zones/volume nodes or moving VWAP discounts; shorts at supply/VWAP premiums.
Risk, Sizing, and Scaling
Longevity comes from risk math that keeps you in the game. Brett’s approach is to standardize risk, cap downside, and scale only when the data says so.
- Risk per trade: 0.25–0.50R of daily risk budget; daily loss cap = 2R; weekly loss cap = 5R; stop trading when either hits.
- Position sizing = Account_Risk_per_Trade ÷ (Entry − Invalidation). Round down; never widen stops to fit size.
- Start at half-size for new or recently tweaked setups; graduate to full-size after ≥60% plan adherence and positive expectancy over 40 trades.
- Add to winners only after new structure forms (higher low for longs / lower high for shorts) and move stop to keep total risk ≤ original 1R.
- Cut risk to 50% of normal after any 3R day or −4R rolling 3-day stretch.
Execution Tactics: From Entry to Exit
Process precision beats bravado. These rules tighten your entry/exit, so outcome variance drops and expectancy rises.
- Wait for the market to trade away from your level, then back to it—enter on the “second chance” to avoid first-touch whipsaws.
- Use a two-target plan: scale 1 at +1R to pay risk; trail the remainder behind structure (swing low/high, session VWAP band, or 20EMA on your execution timeframe).
- If price reaches +1.5R, then closes back through your trigger level, exit remainder—idea likely failed.
- Time stops with structure, not clock: move to break-even only after the first higher low/lower high forms.
- If the catalyst fades (e.g., absorption disappears, volume dries up), tighten the leash even if the price hasn’t hit the stop.
Daily Preparation & Game Plan
Brett’s best performers win their day before the open. Prep builds context so you recognize your edge in real time.
- Pre-market: define bias for three scenarios (trend, balanced, volatile reversal). For each, note the specific setup that would trigger you.
- Mark levels: prior day high/low, value area, overnight extremes, session VWAP, and one higher timeframe inflection (weekly level or multi-day node).
- Write a one-page plan with 2–3 “A” trades you will take and 2–3 traps you will avoid.
- Set a max of 3 executed ideas per session; if you need more, your criteria are too loose.
- Review five minutes before the bell: visualize best/worst case for your top setup and your exact exit if proven wrong.
Review Loop: Journaling That Actually Improves You
Brett’s hallmark is turning experience into skill via rapid feedback. These rules make your review short, sharp, and useful.
- After each trade, tag: setup name, context, adherence (Y/N), emotion (1–5), and any execution slip.
- End of day: screenshot entry/exit with notes on thesis, evidence, and what invalidated/validated the idea.
- Weekly: compute expectancy and adherence by setup; keep only the edges with both positive expectancy and ≥85% adherence.
- Identify 1 micro-skill to practice next week (e.g., “wait for second pullback before adding”) and track reps like a gym log.
- Record a 60-second audio debrief to cement the lesson and prime tomorrow’s behavior.
Psychology: State Management on Command
Brett’s psychology isn’t a pep talk—it’s state engineering. Get yourself into the right mode before, during, and after risk.
- Pre-trade: 2 minutes of paced breathing (inhale 4s, exhale 6s) + one cue word that anchors your best state (“execute”).
- During trade: if heart rate or tension spikes, step away for 60 seconds; return only if the plan still stands.
- Use “if-then” scripts: “If I feel FOMO on a missed move, then I write the missed thesis and wait for a second-chance entry.”
- Protect life outside markets: schedule one non-market win daily (workout, family, hobby) to reduce P&L over-attachment.
- When tilt hits: hard stop after two consecutive rule breaks; resume only after a written reset plan.
Building the Playbook (Templates Included)
Your playbook is a living catalog of edges. Brett’s approach is to template everything so your brain recognizes edges faster.
- For each setup, log: name, market/timeframe, catalyst, confirmation, entry trigger, invalidation, initial target, add-criteria, exit-criteria.
- Include 5 exemplar charts with annotations for both winners and losers.
- Define “no-trade” conditions (e.g., pre-FOMC chop, low ADR session, earnings windows) to save mental capital.
- Run a quarterly “playbook cull”: delete the bottom 20% setups by expectancy/adherence to keep focus sharp.
- Keep a “sandbox” page for experiments; trade sandbox ideas at 25–50% risk until proven.
Multi-Timeframe Context & Market Selection
Edges live in context. Brett encourages aligning the execution timeframe with a higher-timeframe narrative so your trades ride the right wave.
- Trade execution on your best-reading timeframe (e.g., 5–15min for intraday, 1–4h for swing); get bias from 4× higher timeframe.
- Only long when the execution timeframe structure is up, and a higher timeframe shows rising value/acceptance; a mirror for shorts.
- Filter markets by realized volatility relative to your stop size; avoid names where average excursion < 1.2× intended R multiple.
- Rotate to 2–3 instruments where your setups show the cleanest structure; don’t chase everything.
- If a higher timeframe is balanced and your setup is trend-dependent, size down or pass.
Drawdown Protocol and Rapid Recovery
Pros survive by cutting the left tail. Brett’s drawdown rules get you back to baseline without compounding damage.
- At −5R rolling, reduce size to 50% and restrict to A-setups only.
- At −8R rolling, stop for the day(s), conduct a full forensic review, and simulate 20 sample trades before resuming.
- Resume at 50% size until two consecutive green days with ≥90% rule adherence.
- No new setup experimentation during a drawdown.
- If rule breaks caused >50% of the drawdown, implement an external constraint (account lockout, accountability check-in) for 10 trading days.
Mentorship, Deliberate Practice, and Improvement Metrics
Brett’s coaching centers on deliberate practice: isolate skills, get feedback, measure progress. Here’s how to operationalize that solo or with a mentor.
- Pick one micro-skill per week (e.g., “recognize absorption at prior high”) and schedule 20 chart reps with scorecards (hit/miss, confidence, outcome).
- Use weekly KPIs: rule adherence ≥90%, commissions/fees ≤15% of gross, average adverse excursion ≤0.6R, and time-in-trade aligned with plan.
- Record two trades per week as full case studies (prep, execution, management, result, lesson).
- Do a monthly “edge renewal”: re-test assumptions against fresh data; retire edges that lose seasonality or structural tailwind.
- Maintain a small circle for feedback (peer or mentor) and commit to one live review call or written critique each week.
Practical Tech Stack & Checklists
Keep tools simple and habit-friendly. Brett’s ethos is to make the right action the easy action.
- Charts: one higher-timeframe, one execution timeframe, one order-flow/volume view; hide indicators that don’t drive decisions.
- Checklists: pre-trade (context, catalyst, confirmation, location, invalidation), in-trade (risk unchanged? structure intact?), post-trade (tag, screenshot, note).
- Alerts over staring: set price/volume/VWAP alerts for your levels to reduce overtrading.
- Journal in a structured sheet or app with auto-tags; export weekly for expectancy math.
- Backups: template your playbook and journal; copy to cloud at week’s end to preserve continuity.
Optional Swing Overlay (For Intraday Traders Who Want a Second Edge)
Many of Brett’s top performers pair intraday precision with a slower swing framework. This gives you diversification by timeframe without diluting focus.
- Identify 1–2 swing catalysts (earnings drift, macro trend, seasonality) and execute on 4h/day with the same risk rules.
- Hedge swing risk intraday: if day context contradicts the swing, trade in a smaller size or sit out to avoid cross-contamination.
- Swing sizing max = 1.5× intraday R; cap aggregate risk across both books at 2R/day and 5R/week.
- Weekly review: treat the swing book as a separate strategy with its own expectancy and adherence.
- Kill switch: if swing book underperforms intraday by >3R over a month, pause and reassess edge definition.
Size Risk First: Normalize R, cap drawdowns, protect longevity.
Brett Steenbarger starts with one non-negotiable: risk is the only input you fully control. Normalize every trade to a fixed R so your sizing scales with distance to invalidation, not emotion or hope. When R is constant, your journal, expectancy math, and edge comparisons all become clean and comparable. That clarity is what keeps you from nudging stops wider just to fit more size.
Steenbarger also insists on hard loss caps to prevent one bad stretch from rewriting your month. A daily max of 2R and a weekly max of 5R forces you to step back when your read is off. New or recently tweaked setups start at half-size until they prove positive expectancy over a solid sample. The result is boring by design: steady risk, smaller holes, and the staying power to let skill—not variance—drive your equity curve.
Trade Volatility, Not Hopes: Adjust allocation to realized regime.
Brett Steenbarger reminds traders that markets pay based on movement, not wishes. When realized volatility expands, you can earn more with less size; when it contracts, you need tighter targets and smaller expectations. He suggests scaling position size inversely to average true range (ATR) or average daily range (ADR) so you’re not taking the same risk in a quiet tape as in a wild one. That simple adjustment keeps your R multiple consistent whether the market is sleepy or stormy.
Steenbarger also advocates switching tactics with the regime instead of forcing one playbook. In high volatility, favor breakout-continuation with partial profits at +1R and trailers; in low volatility, bias to mean reversion at clear levels with quicker exits. If a volatility filter (e.g., 10-day ATR above/below a threshold) flips, your allocations and expectations flip with it. This way, you’re trading what the market is actually offering, not what you hoped it would do.
Diversify By Underlying, Strategy, and Timeframe to Smooth Equity
Brett Steenbarger pushes traders to diversify on purpose, not by accident. That means running uncorrelated engines: different underlyings, different trade types, and different holding periods, so one rough patch doesn’t swamp your month. Pair an intraday mean-reversion setup in indices with a swing trend setup in commodities or FX; let each book hunt different edges. When correlations spike, cut exposure across the board and keep total risk within a fixed weekly R to prevent hidden concentration.
Steenbarger’s rule is simple: prove each stream’s positive expectancy on its own, then cap any single stream at a maximum share of your risk budget. If your equity curve is being dragged by one market or one tactic, you’re not diversified—you’re diluted. Rebalance weekly: shift risk toward the streams with clean execution and current edge, trim or pause those slipping below adherence or expectancy thresholds. Over time, this intentional spread of bets turns a lumpy P&L into a steadier climb without chasing more trades.
Mechanics Over Prediction: Define setups, manage undefined risk, execute exits
Brett Steenbarger stresses that your edge lives in mechanics, not in guessing the future. Write your setup like code: context, trigger, entry, invalidation, targets—no fuzzy parts. Enter only when the market gives the “second-chance” touch back to your level, not the first emotional poke. Stops go at the price that disproves the thesis, never where the loss simply feels comfortable.
Manage undefined risk by refusing to hold through events that can gap beyond your stop—news, earnings, major data prints—unless your plan explicitly accounts for that slippage. Pay yourself at +1R to neutralize risk, then trail behind structure so one winner can cover many scratches. If structure breaks—VWAP recapture against you, loss of momentum, or failed re-test—exit immediately and log the rule you violated or honored. The goal, as Steenbarger puts it, is a repeatable execution engine that survives bad calls because the mechanics always fire the same way.
Ruthless Process Discipline: Pre-plan sessions, journal, review, upgrade edges
Brett Steenbarger argues that discipline isn’t a mood; it’s a checklist you execute every single day. Before the open, define your three market scenarios, the exact setups you’ll take in each, and the traps you’ll avoid. Put your invalidation levels on the chart and set alerts so you’re reacting to rules, not noise. If a setup doesn’t meet your written criteria, it’s not a pass—no exceptions.
During and after the session, Steenbarger wants fast feedback loops that actually change behavior. Tag every trade with setup name, context, adherence, and emotion score, then screenshot entries and exits with notes. Each week, compute the expectancy per setup and kill or fix the ones dragging your curve. Promote edges that show positive expectancy and ≥90% rule adherence; demote everything else to half-risk or sandbox. The result is a living playbook that upgrades itself because your process forces it to.
In the end, Brett Steenbarger’s message is disarmingly simple: think like a professional, act like a performer, and let the math of risk do the heavy lifting. He keeps sizing expressed as a fixed percentage, so growth never tempts you into sloppy bets, and he treats each trade as a testable hypothesis with a clean invalidation. What stands out across the whole conversation is how relentlessly he turns ambiguity into structure—context, trigger, entry, stop, and exit—so results come from repeatable mechanics rather than lucky predictions. Psychology isn’t a pep talk; it’s practical state management and honest self-assessment that keep you executing the plan when the market gets loud.
Steenbarger also pushes for adaptability without style drift: align tactics with the volatility regime, diversify by instrument and timeframe to smooth the curve, and scale only after the edge proves itself over a real sample. He insists on a tight feedback loop—journals, screenshots, expectancy by setup—so you either upgrade the process or cut the dead wood. And when drawdowns hit, he applies predefined brakes and forensic reviews to stop compounding errors. Put together, his playbook is a blueprint for longevity: small, controlled risks; mechanics that survive bad calls; and a daily process that steadily turns experience into skill.
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