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This interview features Dr. Van Tharp—legendary trading psychologist and author—sitting down with Etienne Crête on the Desire To Trade podcast to unpack why most traders don’t fail for lack of a setup, but for lack of self-awareness. Van’s known for modeling top performers, turning fuzzy “edge” talk into concrete processes, and helping traders connect beliefs, mental states, and rules to real-world results. If you’ve ever wondered why two people can run the same system and get wildly different outcomes, this is the conversation that explains it.
In this piece, you’ll learn Van’s core ideas in plain English: why you “never trade the market—you trade your beliefs,” how to set clear objectives before you touch a chart, and the role of position sizing (think: risk about 1% with pre-planned exits) in making or breaking a system. We’ll hit market types and why one strategy won’t pay in all regimes, how to write rules you can follow, and how tracking mistakes in R-multiples can halve—or double—your performance. You’ll walk away with a blueprint to align psychology, process, and risk so your trader strategy actually compounds.
Dr. Van Tharp Playbook & Strategy: How He Actually Trades
Set Clear Objectives And Beliefs Before Touching A Chart
You don’t trade the market—you trade your beliefs. Van starts by making the end goal explicit, so every rule aligns with it. When you know what you want (income, growth, low drawdowns), you can design the system and risk to match.
- Define one primary objective (e.g., “compound at 25% per year with max 10% drawdown”).
- Write your beliefs about markets, edges, and risk; highlight which ones are testable.
- Eliminate beliefs you cannot operationalize; convert the rest into rules.
- Choose the market universe that best fits your objective (futures, FX, equities, options).
- Specify your holding period and trading frequency in advance (intraday, swing, position).
- Commit to never violating objectives to chase trades—objectives are the north star.
Identify Market Type And Trade Only When Your Edge Fits
Van stresses that most systems are regime-dependent. Label the market first; trade second. If the type is wrong for your strategy, you stand down or switch to the version designed for that environment.
- Classify market type daily/weekly: bullish normal, bullish volatile, sideways quiet, sideways volatile, bearish normal, bearish volatile.
- Pre-map which strategies are allowed in each type (e.g., breakout only in bullish normal/volatile).
- Use objective measures: ATR% or stdev bands for volatility; moving average slope or Donchian state for direction.
- If the market type is “unclear,” trade half-size or don’t trade.
- Reassess type on a fixed schedule (e.g., daily at close, weekly on Friday).
Build A Simple, Rules-Based Entry You Can Execute Consistently
Entries don’t have to be fancy—just consistent and testable. Van prefers rules that are easy to run the same way every time, so your results reflect the system, not your mood.
- Define your setup, trigger, and confirmation as three separate checks.
- Example (trend continuation): setup = price above 50DMA, trigger = 20-day breakout, confirmation = volume above 20-day average.
- Reject discretionary overrides unless they’re formally codified and back-checked.
- Predefine invalidation: if the trigger fails within N bars, cancel the order.
- Put entry logic in a one-page checklist; if any box is unchecked, no trade.
Position Sizing: Make 1R Meaningful And Small Enough To Survive
Position sizing is Van’s “secret sauce.” The same entry with different position sizing yields different equity curves. Keep risk per trade small, denominate everything in R (risk units), and let math protect you.
- Define 1R = initial stop distance × position size = fixed fraction of equity (e.g., 0.5%–1.0%).
- Risk is a constant percentage per trade; do not increase R after a losing streak.
- Use ATR-based stops so 1R adapts to volatility; place initial stop where the setup is invalid, not where it “feels” safe.
- Cap total heat: sum of open risks ≤ 3R (or your chosen heat cap).
- If equity falls by 10%, reduce R by 25% until you recover; treat this as an automatic circuit breaker.
Exit Logic: Pre-Write The Script For Both Good And Bad Outcomes
Exits are where expectancy lives. Van wants exits that are defined before entry and executed without debate. Have a loss exit, a time exit, and a profit-taking or trailing exit.
- Loss exit: initial stop at invalidation; move to breakeven only after objective structure break (e.g., HH/HL sequence).
- Time exit: if price fails to move +0.5R within N bars/days, close the trade.
- Profit exit: partial at +2R, trail remainder with a multiple-ATR stop or last swing low/high.
- Never widen a stop; only tighten.
- If slippage gaps you past the stop, record the extra loss as part of R for journaling.
Expectancy And System Quality Number (SQN)
You need numbers to trust your system. Expectancy and SQN quantify edge quality and smoothness so you know when a strategy is tradable and when it needs work.
- Track every trade in R-multiples; compute expectancy = average R per trade.
- Require at least 30–50 trades of forward data before scaling risk.
- Compute SQN over the last 100 trades; pause or reduce size if SQN drops below your minimum threshold.
- Maintain separate expectancy/SQN per market type; don’t mix regimes.
Daily State Management: Trade Your Plan, Not Your Emotions
Van emphasizes mental states as part of the system. If your state is off, expectancy collapses. Build a routine that sets your state before you risk capital.
- Pre-market checklist: sleep ≥ 7 hours, zero alcohol, breath/centering, review of objectives, and today’s market type.
- No trade if you score your state below a predefined threshold (e.g., <7/10).
- Use a short ritual before each order (breath pattern or cue word) to reduce impulsivity.
- After-session decompression: quick review of mistakes and corrections to close mental loops.
Mistake Control: Cut Error Rate To Raise Expectancy
Van treats mistakes as separate from losses. A loss without mistakes is fine; a profit with mistakes is dangerous. Lowering mistake frequency directly improves results.
- Define your “Top 5” mistakes (e.g., skipped stop, oversizing, discretionary override).
- Tag each trade as “no-mistake” or “mistake,” then compute expectancy for both.
- If the mistake rate > 5% across the last 20 trades, reduce risk by 50% and drill checklists.
- Run a weekly mistake post-mortem and add one process fix; never add more than one fix per week.
Portfolio Heat, Correlation, And Position Limits
Great systems can still drown in correlated exposure. Van caps portfolio risk and controls clustering so one theme doesn’t sink the ship.
- Limit simultaneous positions in the same market type or sector (e.g., max 2 positions per sector).
- Use rolling 60-day correlation to size down overlapping names; if corr > 0.7, count as 1.5 slots.
- Enforce max open risk (heat) and a daily loss limit (e.g., 2R/day).
- If the daily loss limit hits, stop trading for 24 hours and review.
Scaling Rules: Earn The Right To Increase Size
Size is a privilege you earn with data. Van grows exposure only when the system proves itself under current conditions.
- Increase R by 10–20% only after 50 additional trades with SQN above target and max drawdown within objective.
- Add markets one at a time; require the same performance gates per symbol.
- If you hit a new equity high, lock in a baseline (e.g., trail a “risk budget” floor) to avoid giving back months of gains.
Playbook In One Page (Operational Checklist)
This is the at-desk script you’ll follow. Keep it visible and run it line by line so execution is clean and repeatable.
- Confirm objective and market type; if a mismatch, no trade.
- Locate setups that match today’s type; apply the exact entry checklist.
- Set initial stop and position size to risk exactly 1R.
- Place orders; set alerts; document planned exits (loss/time/profit).
- After the close, log R-multiple, market type, mistakes, and state score.
- Weekly: review expectancy/SQN by market type; adjust size or pause if thresholds are breached.
Set Objectives and Beliefs First, Then Design Your Trading System
Dr. Van Tharp insists you start with the destination, not the indicator. Define what you want—monthly income, long-term compounding, or minimal drawdowns—and make every rule serve that target. Then write down your beliefs about markets and edges so they’re visible, testable, and fixable. If a belief can’t be turned into a rule, it doesn’t belong in your trading.
With objectives set, design the system backward: market universe, holding period, setups, entries, exits, and position sizing that all align with the goal. Keep language plain so you can execute on a tired Monday exactly like a fresh Friday. Review beliefs quarterly to remove what didn’t hold up and promote what did. This is how Dr. Van Tharp turns fuzzy intentions into a trader’s daily playbook.
Size Positions in R; Risk Small, Survive Volatility and Drawdowns
Dr. Van Tharp teaches that every decision becomes cleaner when your risk is measured in R. Define 1R as the dollars you lose if the initial stop is hit, then keep R small so variance can’t knock you out. Most traders do best risking 0.5%–1.0% per trade, letting the math—not emotions—dictate size. Use volatility, like ATR, to set stops where the setup is invalid, not where it simply “feels safe.” When you think in R, outcomes become comparable across markets and timeframes.
Consistency beats bravado, so keep a constant-R approach until the data proves you’ve earned a bigger size. Cap portfolio heat by limiting total open risk, and cut size automatically after a drawdown to protect the equity curve. Let winners expand account equity and only then lift R carefully, never during a cold streak. This is how Dr. Van Tharp turns position sizing into the compounder behind your edge.
Match Strategy To Market Type; Stand Down When Edge Misaligns
Dr. Van Tharp stresses that your edge is conditional on the environment, not permanent truth. Label the market first—trending or sideways, quiet or volatile—then run only the strategies built for that label. If the type is unclear, he’d rather you reduce the size or skip the trade than force a setup into the wrong regime. This protects expectancy and keeps you from blaming a valid system for a mismatched market.
Once the type is set, your rules decide everything: which setups are allowed, what confirmation you require, and how far the initial stop must live. When conditions shift, you either switch to the version of the system meant for that regime or you go flat. Dr. Van Tharp’s point is simple: discipline is the filter that keeps a good strategy good. The restraint to stand down is as valuable as the trigger to get in.
Diversify By Underlying, Strategy, And Duration; Cap Portfolio Heat
Dr. Van Tharp pushes diversification that actually reduces risk, not the kind that just adds clutter. Spread exposure across uncorrelated underlyings, mix strategies that win in different regimes, and stagger holding periods so not everything breathes the same volatility at once. Treat correlation like a position in disguise—two highly correlated trades can equal one oversized bet. The aim is smoother equity and fewer wipeout days when one theme reverses hard.
Then police “portfolio heat,” the sum of all open risk, so a bad afternoon can’t ruin your month. Set a firm cap—like 3R total—and refuse to exceed it, even if the next setup looks perfect. If heat swells or correlations spike, cut positions or resize proactively. That’s how Dr. Van Tharp keeps diversification purposeful and the account resilient when markets get loud.
Measure Expectancy And SQN; Reduce Mistakes With Process Discipline
Dr. Van Tharp treats performance as math first, ego last. He wants every trade logged in R, so expectancy—the average R per trade—tells you if the strategy actually pays. Calculate it weekly and by market type so you can see where the edge lives and where it dies. When expectancy slips or goes negative, you don’t argue; you reduce size or pause and fix the rule that failed. This simple loop keeps you scaling what works and pruning what doesn’t.
To keep quality high, he uses SQN, a score of system smoothness over a rolling sample. If SQN drops below your floor, you either tighten rules, cut markets, or stand down until conditions realign. Just as important, he separates losses from mistakes, because a clean 1R is fine, but a sloppy +1R can poison discipline. By attacking mistake rate and watching expectancy and SQN together, Dr. Van Tharp turns trading into a controlled experiment that compounds results instead of emotions.
In the end, Dr. Van Tharp keeps bringing you back to ownership: your beliefs, your objectives, and your rules create your results. Start with a written business plan that spells out why you trade, the returns and max drawdown you accept, and the market types you’ll allow yourself to play. Build at least three non-correlated systems designed for different regimes because one setup won’t pay in all six market types. Then let position sizing do the heavy lifting—define 1R, risk small, cap total heat, and make exits mechanical so expectancy comes from math, not impulse.
He also reframes “failure” as process gaps you can fix. A mistake isn’t a loss; it’s breaking a rule. Track every trade in R-multiples, log mistakes separately, and work the error rate down from double digits to something you can live with. Pair that with simple state management—sleep, a pre-trade checklist, and a daily review—and you’ll start trading your plan the same way on a bad day as on a good one. That’s the lesson set: beliefs to objectives, objectives to rules, rules to sizing, sizing to steady equity—the practical path Dr. Van Tharp lays out for traders who want results they can repeat.
