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This interview features Michael Berman—ex-hedge fund trader, co-founder of PsyQuation, and long-time markets operator—recorded at AxiTrader’s Sydney office with Etienne speaking. Berman blends behavioral finance with quantitative rigor, drawing on years running capital, building the RAPA platform, and launching PsyQuation in 2016 to help traders reduce mistakes and earn more consistently. He’s refreshingly blunt about the craft: there’s no holy grail, your edge lives at the margins, and risk management decides whether you “eat what you kill.”
In this piece, you’ll learn Berman’s practical framework for building edge: how PsyQuation’s alerts catch costly habits, why its merit-based score and incubation pathway matter, and the thresholds that unlock funding as your discipline improves. We’ll unpack his takes on the disposition effect (it’s not always “bad”), the dangers of martingale thinking, smarter use of sentiment via order-flow segmentation (OFSI), and why diversification beats hero worship. If you’re a retail trader trying to turn decent ideas into durable results, Berman’s strategy toolbox shows how to measure skill, minimize errors, and compound a small advantage into real returns.
Michael Berman Playbook & Strategy: How He Actually Trades
Edge, Defined First
Before pushing buttons, Michael Berman starts by defining where the advantage truly lives. He treats “edge” as a small, persistent expectancy that only shows up when it’s measured and repeated—never as a one-off hunch. This section spells out how to turn a fuzzy idea into a testable play that compounds over time.
- Write a one-sentence edge statement: “I profit when X setup appears in Y regime because Z mispricing repeats.”
- Quantify expectancy: log win rate, average win, average loss, and compute (E = p \times \bar{W} – (1-p) \times \bar{L}).
- Demand a minimum positive expectancy (e.g., > 0.15R) over at least 100 trades before increasing risk.
- Identify the market condition where your edge dies (e.g., low-vol chop) and set a “do-not-trade” tag for that regime.
- Re-validate quarterly; if expectancy decays for two consecutive review cycles, pause and re-specify the edge.
Risk Sizing That Survives
Berman is unapologetically risk-first. He sizes positions so a bad run doesn’t knock the trader out, because survival is the only path to compounding. Use these rules to keep losses tolerable and math on your side.
- Risk a fixed fraction of equity per trade (e.g., 0.25%–0.75%); never scale risk with “confidence.”
- Cap portfolio “risk-on” at a hard ceiling (e.g., 3% total open trade risk across all positions).
- Pre-define stop distance from market structure (ATR, swing level) and back into position size; never move a stop further.
- If daily drawdown hits −2R or equity down −2%, stop trading for the session (“circuit breaker”).
- Reduce unit size by 50% after any 6R weekly drawdown until the equity curve recovers prior high.
Entries, Exits, and R-Multiples
He treats entries as cheap options on an idea and exits as the engine of expectancy. The goal is to standardize how much you lose when wrong and let the right-tail do the lifting.
- Enter only when your setup AND market regime align; skip late signals after a 2R move has already happened.
- Use 1R as initial stop (based on structure/volatility); place take-profit as a bracket, not a guess.
- Scale out only if it increases expectancy in backtests; otherwise hold for pre-set targets or trailing logic.
- Promote trades to breakeven after +1R only if your data shows improved expectancy; otherwise keep original stop.
- Close the trade immediately on thesis violation (structure break, regime flip), not on “feel.”
Drawdown Governance & Equity-Curve Rules
Berman treats the equity curve like a vital sign. He uses mechanical brakes so a cold streak doesn’t spiral into account damage.
- Maintain a written max peak-to-trough drawdown limit (e.g., 10%); at breach, mandate a 2-week trading break and review.
- Switch to “probation size” (e.g., 0.25% risk) anytime you record three consecutive losing days.
- Ban revenge trading: if you re-enter within 5 minutes of a stop-out, log a rule violation and auto-reduce size next trade.
- Use a rolling 30-trade expectancy; if it turns negative, trade only your single best setup until it’s positive again.
- Track “equity heat” (sum of open risk); if > 3% of equity, stop adding exposure regardless of how good new signals look.
Behavioral Error Alerts
His edge isn’t just the setup—it’s the removal of costly human errors. Build simple guardrails that trigger when your behavior drifts.
- Set automated checks for: adding to losers, widening stops, over-sizing, skipping logs, and trading outside hours.
- If two behavior alerts trigger in a session, shut down for the day; journal the incident before the next session.
- Define “tilt conditions” (sleep < 6 hrs, big life stress, missed workout) and halve risk on those days.
- Force a 60-second pre-trade checklist: setup match, regime match, risk size, stop location, exit plan.
- Enforce a 10-minute “cool-off” after any >2R loss before the next order submission.
Data, Journaling, and Feedback Loops
Berman’s process is data-driven: what gets measured gets improved. You need a feedback loop that exposes which behaviors and setups actually pay.
- Log every trade with: setup label, regime, R-multiple, MAE/MFE, and checklist pass/fail.
- Review weekly: top 3 money-making behaviors and top 3 money-losing behaviors; convert each into a do-more/stop-doing rule.
- Calculate per-setup expectancy and kill the bottom decile of setups each month.
- Track time-of-day and day-of-week performance; blacklist your worst two slots for new entries.
- Use distribution, not average: study the R-histogram to see if a few big winners carry the system; protect the right-tail.
Portfolio Construction & Correlation Control
He diversifies by strategy and instrument rather than simply adding more of the same exposure. The aim is a smoother equity curve with multiple independent edges.
- Limit any single instrument to 30% of open risk and any single strategy to 50% of total risk.
- Tag assets by cluster (e.g., USD, rates, index beta, energy); avoid stacking positions in the same cluster.
- Run at least two uncorrelated strategies (e.g., mean-reversion and breakout) to reduce equity swings.
- If rolling 20-day correlation between two strategies > 0.6, temporarily disable the weaker one.
- Prefer smaller positions across uncorrelated bets instead of one concentrated hero trade.
Scaling Rules: Earn the Right to Size Up
Berman favors merit-based scaling: size grows only when the process proves it can handle it. These rules protect you from “premature size.”
- Increase risk per trade by 0.1% only after 100 trades with positive expectancy and drawdown within plan.
- Scale exposure when equity makes new highs, not during a drawdown.
- Add capital or external funding only after three consecutive profitable quarters at target risk.
- Treat sudden windfalls as sampling noise; hold size steady until expectancy stabilizes at the new level.
- Tie compensation to R, not dollars, to prevent goalpost-moving when capital changes.
Strategy Maintenance & Version Control
He treats a trading strategy like software: versioned, documented, and updated with intent—not impulse. That structure keeps the edge from drifting.
- Maintain a simple “strategy spec” (objective, indicators, regime filter, entry, exit, risk, notes) with a version number.
- Allow just one controlled change per review period; test it for 50–100 trades before adopting.
- If a change fails to improve expectancy, revert to the prior version immediately.
- Archive dead strategies with a post-mortem so the same mistakes aren’t repeated.
- Schedule monthly “delete day” to remove redundant indicators, rules, and dashboards.
Practical Trade Management Templates
Berman’s approach shines in standardized templates—fast to execute, easy to audit. Use these plug-and-play rules to cut friction.
- Breakout template: enter on close above/below key level with ATR-based stop (1.5–2.0 ATR); target 2–3R or trail by 1 ATR.
- Mean-reversion template: fade extreme with limit order only when regime is range-bound; stop beyond swing extreme; partial out at 1R, trail remainder.
- News template: trade only if the setup existed pre-news; if slippage > 0.5R on fill, reduce position by half immediately.
- Overnight policy: if VIX (or asset vol proxy) is above your threshold, close partial before the close to cut gap risk.
- Weekend policy: hold only if position is > +1R with protective stop already locked beyond breakeven.
Personal Operating System
Finally, he runs himself like part of the system—because the trader is the biggest variable. These habits keep the operator consistent.
- Define trading hours and forbid ad-hoc sessions; consistency beats sporadic “opportunity.”
- Pre-market routine: 15-minute market scan, regime tag, top-3 watchlist with triggers written out.
- Post-market routine: reconcile fills, tag errors, update equity heat, and shortlist next session’s levels.
- Physical baseline: minimum sleep, hydration, and movement targets; break risk by 50% if any baseline misses.
- Weekly reset: one hour every weekend to review stats, tweak alerts, and set the single improvement goal for the week.
Size Risk First: Fixed R, circuit breakers, survive losing streaks
Michael Berman hammers home that survival comes before brilliance, and that starts with fixed-R risk per trade. He treats position size as a hard rule, not a feeling, so the worst case is always known before entry. A simple daily circuit breaker—stop trading after a defined loss—prevents a bad day from becoming a career-ending spiral. By standardizing risk, you protect the equity curve long enough for small edges to actually show up.
Berman also plans for losing streaks like they’re guaranteed, not hypothetical. When the tape turns, he cuts unit size automatically and lets the system cool instead of chasing it back. He only scales up after the account makes fresh highs, never during drawdown, which keeps emotions from hijacking the math. In short, Michael Berman’s first commandment is boring by design: control R, respect the brakes, and live to take the next high-quality trade.
Trade Mechanics Over Predictions: codify setups, regime filters, standardized exits
Michael Berman argues that predictions are entertainment, while mechanics pay the bills. He codifies each setup into plain rules—trigger, invalidation, stop distance, initial target—so entries are repeatable. A regime filter decides when the setup is even allowed, because the same pattern behaves differently in trend versus chop. Once rules exist, discretion moves from “guessing direction” to “executing a checklist.”
Berman standardizes exits to protect expectancy, not to soothe nerves. He picks one exit logic per setup—fixed R targets, trailing ATR, or structure-based—and runs it consistently enough to generate reliable stats. If an exit tweak doesn’t lift expectancy over 50–100 trades, it’s out. In Berman’s world, prediction is optional; mechanical execution is mandatory.
Volatility-Based Positioning: ATR stops, dynamic unit sizes, controlled equity heat
Michael Berman treats volatility as the steering wheel for risk, not a background statistic. He sizes positions off ATR or recent range so that a “1R” stop reflects current conditions, not yesterday’s calm. When markets expand, unit size shrinks; when they quiet down, unit size can grow—always to keep the same risk in R terms. This keeps the stop meaningful and the math consistent across regimes.
Berman also caps “equity heat,” the total open risk across positions, so one busy session doesn’t sneak past his pain threshold. He avoids stacking correlated bets; if vol spikes and correlations tighten, he trims or staggers entries. Trailing stops ratchet with volatility, locking progress without suffocating the trade. In short, Michael Berman lets volatility tell him how big to play, how many to hold, and when to cool it.
Diversify By Strategy, Underlying, And Timeframe To Smooth Equity Curve
Michael Berman pushes diversification beyond “more tickers” into genuinely different return drivers. He blends uncorrelated strategies—say, breakout and mean reversion—so one thrives when the other rests. Underlyings are grouped by risk clusters (USD, index beta, energy, rates), and he caps exposure per cluster to avoid hidden concentration. Timeframes are staggered—intraday, swing, and position—so outcomes aren’t decided by a single market rhythm.
Berman also watches rolling correlation; if two strategies start moving together, he parks the weaker one until independence returns. He spreads risk across instruments with different vol profiles and refuses to stack trades that respond to the same macro shock. When correlations compress during stress, he cuts aggregate heat first, not last. The aim, according to Michael Berman, is a smoother equity curve built on several small engines, not one noisy motor.
Define Edge Clearly, Measure Expectancy, Scale Only On New Equity Highs
Michael Berman starts with a crisp edge statement so there’s no mystery about why a setup should pay. He then measures expectancy in R terms—win rate, average win, average loss—until the numbers prove the thesis. No scaling, no fanfare, just repeatable execution over a meaningful sample. If expectancy slips for a stretch, he pauses the setup and fixes the leak before another dollar is risked.
When the stats hold and the equity curve prints a genuine new high, that’s when Berman allows a small size bump. He never scales during drawdowns because that’s when psychology is most dangerous and variance is lying the loudest. The rule is anti-martingale in spirit: earn the right to bet bigger only when the account validates the process. In Michael Berman’s playbook, clarity, measurement, and disciplined scaling turn a tiny edge into a durable business.
In the end, Michael Berman’s message is refreshingly simple: there’s no holy grail—there’s a process. His north star is reducing avoidable mistakes and letting small, measurable edge compound. That’s why he’s relentless about fixed risk, clearly defined setups, and rules that survive real drawdowns. The point isn’t to out-predict the market; it’s to out-execute your former self by turning behavior into guardrails you actually follow.
Berman’s builder mindset shows up everywhere: quantify expectancy, use volatility to size intelligently, and cap total “equity heat” so a busy day doesn’t become a bad month. Diversification means uncorrelated strategies, underlyings, and timeframes—not more of the same bet. And scale is earned, never assumed; you only step up size when the equity curve prints new highs and your stats back it. If you take one lesson from Michael Berman, make it this: engineer your trading like a small business—measure what matters, delete what doesn’t, and let disciplined mechanics do the heavy lifting.
