Table of Contents
In this interview, risk manager and author Michael Toma sits down to unpack the part of trading most people skip: real risk management. Instead of obsessing over single trades or vanity win/loss stats, Michael pushes traders to think in batches of trades, focus on execution compliance, and measure everything against the true boss metric—risk of ruin. If you’ve been chasing entries and ignoring the math that keeps you in the game, this is the conversation you needed.
Read on to learn how Michael Toma reframes risk around series-based analysis, journaling and backtesting, execution-first thinking, and sizing discipline that won’t torch your equity curve. You’ll see why risk–reward is linear (and overrated), how to implement simple controls that make you “suck less” each week, and when you’ve actually earned the right to scale. If you want a trader strategy that survives volatility and compounds consistency, start here.
Michael Toma Playbook & Strategy: How He Actually Trades
Core Philosophy: Risk is the product, not the trade
Trading works when your risk process works. Michael Toma frames everything around protecting the account first and letting the math of repeatable decisions do the heavy lifting. Think “execute a process” — not “predict a chart.”
- Define a fixed fractional risk per trade (e.g., 0.25%–0.75% of equity) and never exceed it.
- Cap total open risk at any moment (e.g., ≤1.5% of equity across all positions).
- Set a daily loss stop (e.g., 2× your per-trade risk) that ends the session if hit.
- Pre-declare your max weekly drawdown (e.g., 3%–4%); if breached, you drop size and audit execution before resuming.
- Treat “edge” as repeatable behavior measured over a series of trades, not a single outcome.
Position Sizing That Survives Volatility
Sizing is the steering wheel of risk. The goal is to keep losses small and consistent while giving winners room to express. Volatility changes; your size adapts so your risk stays constant.
- Position size = (Account × %Risk) ÷ Stop distance.
- Use market structure or ATR (e.g., 1.5–2.5× ATR) to set stops; never tighten after entry to “fit” size.
- If ATR doubles, your position halves to keep the same dollars at risk.
- Hard rule: never widen stops after entry; if invalidated, exit and log.
- If slippage regularly exceeds 20% of planned risk, reduce the size or avoid that product/session.
Batch-of-Trades Mindset & Compliance Tracking
Edge shows up in batches, not one-offs. Run your trading like a small experiment, grade your execution, and let the statistics speak before you change anything.
- Trade in fixed batches (e.g., 20–30 trades) before evaluating expectancy or making tweaks.
- Track a “compliance score”: Did you follow entry, size, stop, and exit rules? Aim ≥85% per batch.
- Only change rules after a full batch review, never mid-batch.
- If compliance <80%, you don’t have performance data — you have noise. Fix execution first.
- Keep a simple scorecard: setup tag, risk (R), R multiple result, compliance Y/N, lesson.
Entries & Exits: Mechanics Over Prediction
Entries are about context and location; exits are about risk math. Keep both mechanical so your behavior is the same on a bad day as on a great one.
- Enter only when your pre-defined context exists (e.g., pullback to value + momentum resumption).
- Place the stop where the idea is wrong (structure/ATR), not where P&L feels okay.
- Standardize targets (e.g., first scale at +1R only if it improves expectancy; otherwise hold for +2R or trail).
- Trailing rule: trail below/above last confirmed swing or an ATR-based stop; never trail intra-bar.
- If the trade moves +0.8R and then prints your invalidation, exit — no “hope holds.”
Volatility & Session Filters
Not all market hours or regimes are equal. Filter when you trade and how aggressively you size to keep quality high and noise low.
- Trade set sessions only (e.g., first 2 hours of London/NY overlap for FX; RTH for indices).
- Skip the first 5 minutes after major data releases unless that’s your tested edge.
- If realized volatility (ATR) is <50% of its 20-day median, cut size by half or stand down.
- In high-volatility spikes (>150% of 20-day median ATR), reduce size and widen stops proportionally.
- No new positions within 30 minutes of your stop-trading time.
Drawdown Protocols That Prevent Spiral
Drawdowns are part of the game; spirals are optional. Use pre-committed step-downs to protect capital and psychology.
- At −3R day or −5R rolling week, stop trading and conduct an execution audit.
- At −8R batch drawdown, cut risk per trade by 50% for the next 10 trades.
- Regain prior equity high only after two compliant, profitable batches — then you may scale up one notch.
- If two consecutive batches are red with ≥85% compliance, the system (not you) needs refinement; review rules, not mindset.
- Prohibit “revenge trades” by requiring a written pre-trade checklist before the next session resumes.
Scaling Rules: Earn the Right to Size Up
More size magnifies slippage, emotion, and error. Scale only when the data says your process can carry the load.
- Requirement to scale: 2 consecutive positive batches, compliance ≥90%, and PF ≥1.3.
- Increase risk per trade by the smallest increment (e.g., +0.10% of equity) and hold for a full batch.
- If slippage or heat (MAE) expands beyond tested norms after scaling, roll back immediately.
- Add contracts/shares only if the market’s depth supports it during your entry window.
- Re-backtest with current ATR levels before any additional scale-up.
Trade Selection & Diversification by Behavior
Diversify by how trades behave, not by ticker symbols. The aim is to smooth equity and avoid stacking correlated risk.
- Limit simultaneous positions that share the same driver (e.g., USD trend exposure) to one idea.
- Maintain a “driver map” (rates, USD, vol, sector beta) and cap exposure to one dominant driver at a time.
- Require uncorrelated timeframes or setups if holding multiple positions.
- If two setups trigger together and correlation >0.7 historically, take the cleaner one, skip the other.
- Track the rolling 60-day correlation of your realized P&L by setting up to spot hidden concentration.
Journal, Metrics, and Weekly Review
You can’t fix what you don’t measure. Keep the journal lightweight but relentless, and review on a schedule.
- Log each trade with: setup tag, screenshot (optional), R plan, R outcome, compliance, and one sentence lesson.
- Weekly, compute: win rate, average win/loss in R, expectancy, PF, and compliance.
- Flag your top three failure modes (e.g., late entries, moving stops, chasing) and design one rule to remove each.
- If expectancy is negative but compliance ≥85%, your system needs rule edits; if compliance is low, your behavior needs work.
- Archive “A-plus examples” to train pattern recognition and speed up future decisions.
Event & Overnight Risk Controls
News shocks and gaps can break good setups. Build rules for when not to play and how to carry risk when you must.
- Flat into Tier-1 events unless you have tested event strategies; otherwise, close or hedge.
- For overnight holds, cap single-name equity risk at half your intraday risk and prefer index/futures with tighter spreads.
- Use hard stops plus conditional “catastrophe exits” (broker OCO or synthetic) where products allow.
- Avoid illiquid hours for entries; if spread >0.5× your stop, skip the trade.
- If carrying positions into earnings or major macro prints is part of your edge, pre-define hedge size and worst-case loss.
Prop-Style Rules (If Trading With Firm Constraints)
Funding rules change how you express an edge. Protect the account first, then optimize for the prop environment’s metrics.
- Respect daily and trailing drawdown limits by gating size so the worst case on all open trades is <80% of the limit.
- Convert all targets to R so you can meet minimum monthly profit targets without oversizing.
- If a “consistency rule” exists, split entries (e.g., two half-stakes) and smooth the P&L curve.
- Avoid trading during news windows that can invalidate risk limits with a single gap.
- When near a max-loss line, trade half-risk or stand aside until the buffer is rebuilt.
Simple Pre-Trade Checklist (Run in Under 60 Seconds)
Checklists make execution boring — that’s the point. Use it to gate every order and keep your compliance score high.
- Is the setup present? (Yes/No)
- Risk per trade set and position sized? (Yes/No)
- Stop placed at invalidation, target(s) defined in R? (Yes/No)
- Correlation/driver conflict? (If yes, reduce size or skip.)
- Any events within your no-trade window? (If yes, stand down.)
- Screenshot and log prepared? (Yes/No)
Post-Trade Protocol (Fast Debrief, Then Move On)
Close the loop while the trade is fresh, then get back to neutral. This builds the habit that compounds edge.
- Record final R outcome, MAE/MFE, and compliance within 5 minutes of exit.
- Note one concrete improvement (e.g., “enter only on retest to reduce heat”).
- If three similar mistakes appear, add or tighten a rule before the next session.
- End the day if the daily loss stop is hit; no exceptions.
- Plan your first trade for tomorrow before you leave the desk — context, level, and risk pre-written.
Risk Is The Product: Fixed Fraction Sizing That Survives Volatility
Michael Toma treats risk like inventory—guard it and the business lives. He pre-commits to risking a small, fixed fraction of equity on every trade so a bad day can’t snowball into a bad month. The point isn’t to be brave; it’s to be consistent, because compounding only works if you’re still in the game. Fixed-fraction sizing also keeps emotions out of the throttle, so your size doesn’t yo-yo with confidence.
When volatility jumps, Michael Toma doesn’t “feel” smaller—he is smaller, because position size is derived from the same fixed fraction divided by a wider stop. If ATR doubles, the position halves to keep the dollars at risk unchanged. A daily loss stop and a cap on total open risk close the loopholes that blow up otherwise good systems. The payoff is a smoother equity curve and the mental space to execute the next trade exactly like the last one—calm, sized right, and survivable.
Batch Your Trades and Grade Compliance, Not Single-Trade Outcomes
Michael Toma frames performance around batches—think 20 to 30 trades—so variance can’t bully your decision-making. Instead of celebrating wins or mourning losses one by one, he asks a simpler question: Did you follow the plan? By grading compliance for each rule (entry, size, stop, exit), he can separate system quality from trader behavior. This prevents mid-batch tinkering and lets the data show whether the edge exists or the execution leaked.
In practice, Michael Toma sets a compliance threshold—usually north of eighty percent—before trusting any batch’s P&L. If compliance is low, he fixes behavior first; if compliance is high and results still lag, he tunes rules with intention. The batch lens also kills tilt because a single trade can’t “make the month” or “ruin the week.” Over time, the habit of batching creates calmer decision cycles, cleaner journals, and a measurable path to scaling when the numbers—not emotions—say you’ve earned it.
Volatility-Based Position Sizing: ATR Stops, No Widening After Entry
Michael Toma sizes trades off volatility so risk stays constant when markets get loud or quiet. He anchors stops to structure and ATR—typically a multiple like 1.5–2.5×—so the stop lives where the idea is objectively wrong, not where the P&L feels comfortable. Position size is then computed from a fixed fraction of equity divided by that stop distance, which means the dollar risk per trade doesn’t change even as ranges expand. If ATR doubles, the position gets cut roughly in half, preserving the same risk while respecting current conditions.
Just as important, Michael Toma never widens a stop after entry; invalidated means out, period. He’ll trail only on confirmed structure or an ATR-based trail, and never intra-bar where noise can whipsaw discipline. If slippage regularly eats more than a chunk of the planned risk, he reduces the size or avoids that session to protect expectancy. On volatility spikes, he narrows the playbook to A-setups and tightens execution, letting fewer, cleaner trades do the lifting. This combination—ATR-defined space, fixed-fraction sizing, and zero stop-creep—keeps losses small, predictable, and survivable.
Mechanics Over Prediction: Pre-Planned Exits, Trailing Rules, No Hope
Michael Toma treats entries as permission to execute a script, not a license to predict the future. Before he clicks, the exit is already written: invalidation level, profit-taking logic, and the exact conditions that end the trade. That clarity turns each position into a controlled experiment where outcome variance can’t bully behavior. By scripting exits ahead of time, Michael removes the most expensive emotion in trading—hope.
Once in, Michael Toma follows the plan with trailing rules that are objective and slow, never intra-bar. He’ll trail below structure or an ATR-based buffer, ratcheting only after clear confirmation and never because a candle looks scary. If the market tags invalidation, he’s out immediately and logging, not negotiating. Winners are allowed to work without micro-management; losers are cut with consistency. The edge isn’t guessing right, it’s executing the same high-quality mechanics every single time.
Drawdown Protocols and Scaling Rules That Protect Equity And Psyche
When the account slips, Michael Toma switches from offense to preservation mode with pre-committed drawdown steps. He stops trading for the day after a defined loss threshold, then audits execution before touching size. If a batch hits a deeper drawdown, he cuts risk per trade and shortens the playbook to only A-setups. These rules cap damage, protect confidence, and keep the next session from starting in a psychological hole.
Scaling up is earned, never assumed, in Michael Toma’s approach. He requires back-to-back compliant, profitable batches before nudging risk per trade up a notch. After any scale increase, he monitors slippage, heat, and compliance; if any metric degrades, size rolls back immediately. He ties size to market depth and volatility, so bigger doesn’t mean sloppier. The result is a glide path where equity growth is steady, recoveries are controlled, and the psyche stays calm enough to execute the plan.
Michael Toma’s core lesson is simple: risk is the business—you manage that, and the trading takes care of itself. He shifts the focus away from single trades and “win rate worship” to batches of 20–30 trades, where you grade your execution (compliance) and assess whether your process actually reduces your risk of ruin over time. In his words, a bad Tuesday trade doesn’t matter if the series is protected; what matters is whether you executed the plan and whether your rules keep the account survivable through variance.
From there, Michael Toma lays out a practical framework: identify risks, assess their impact, and implement controls—journal relentlessly, test, then tighten rules so you “suck less” each cycle. This means fixing oversizing (the fastest path to ruin), sizing with volatility-aware stops, and using software and metrics to confirm that your tools actually fit you and your lifestyle. He stresses that risk–reward is a linear math choice across a series, so the edge isn’t in a magic ratio; it’s in consistent execution and sizing that match your profile. Start small, minimize errors, and let compliant batches—not emotions—dictate when to scale.
