Table of Contents
In this interview, trader and risk coach Michael Toma sits down with algo specialist Alejandro Perez to unpack a year of lessons from the Desire To Trade team—why risk comes first, how to adapt strategy to your lifestyle, and what actually worked across markets from bonds to crypto. You’ll hear straight from two practitioners who coach, build, and trade: Michael focuses on enterprise-level risk management for traders, while Alejandro turns robust ideas into systematic executions that don’t fall apart the moment the market changes.
Read on to learn how Michael Toma sizes up A+ setups without blowing risk limits, how Alejandro Perez designs and maintains algos that mirror solid price-action principles, and how both of them think about passing prop-firm evaluations without gambling. We’ll cover the nuts and bolts—risk modeling, execution discipline, portfolio-level thinking, and when to simplify versus systematize—so you can pick a trader-friendly process, stick with it, and grow with fewer chart-hours and more consistency.
Michael Toma Playbook & Strategy: How He Actually Trades
Core Risk Framework (the first decision, every trade)
Before Michael Toma looks for entries, he locks in risk. He treats risk as the product he sells—entries just express it. This section lays out his baseline guardrails so you never “guess” size or tolerance mid-trade.
- Define max daily loss (MDL): 1R–2R of average trade risk; stop trading if hit.
- Cap per-trade risk at 0.25%–0.5% of account; 0.25% for choppy conditions.
- Hard stop goes in the system at order entry—no mental stops.
- If spread/volatility widens, halve size or skip—never widen stops to “make it fit.”
- If you take two consecutive rule-breakers, pause for 30 minutes minimum.
A+ Setup Filter (trade less, win more)
He grades setups before touching the DOM. Only A or high-B grades get risk; everything else gets journaled for pattern-building. This keeps your capital concentrated in your edge, not your boredom.
- Predefine “A+” with a checklist score ≥8/10 across trend, structure, catalyst, and liquidity.
- Trade only during your defined session windows; outside hours = automatic pass.
- Require a higher-timeframe confluence (HTF S/R, VWAP bands, or prior day’s value area).
- If expected R multiple <2.0, pass—even if the signal looks pretty.
- One market condition mismatch (e.g., fading a strong trend) drops the grade by 2 points.
Entry Triggers & Timing (let price invite you in)
Michael prefers simple, repeatable triggers that sync with structure and volatility. The aim is to avoid “predicting” and instead let price confirm your idea at logical locations.
- Use limit entries at HTF levels; use stop entries on momentum breaks—never market in on uncertainty.
- Accepted triggers: pullback to VWAP/20EMA with a rejection candle; break-retest of prior high/low; opening range break with retest.
- Enter on the candle that closes with confirmation (wick rejection, body through level, or delta shift)—not mid-bar.
- If the trigger forms >3 ATRs away from your intended stop, skip; location is compromised.
- Missed entry? Do not chase—either wait for the next retest or abandon the idea.
Position Sizing by Volatility (make size dynamic, not emotional)
He scales size with volatility, so the same thesis carries equal risk on quiet and frenetic days. Here’s how to turn ATR into a sizing throttle you can actually use.
- Base stop distance on recent ATR(14) or session ATR(5): stop = 0.8–1.2× ATR of your entry timeframe.
- Compute units = (account × risk%) ÷ stop distance; round down to the nearest lot/contract.
- If VIX (or instrument volatility proxy) is in the top quartile for 30 days, cut size by 30–50%.
- News hour? Reduce risk by 50% unless your setup explicitly relies on the catalyst.
- Never increase size to “make back” losses; only increase after 10R net positive and stable win-rate.
Trade Management & Exits (pre-commit the path)
Michael treats exit logic as part of the entry, not an afterthought. He uses staged profit-taking to fund the trade and let a runner compound the good days.
- Predefine three exits: PT1 at 1R, PT2 at 2R, runner to structure or 3R+.
- Move stop to breakeven only after PT1 is filled and price closes past entry by ≥0.5R.
- If price tags 2R and then reverses to B/E, you still had a good trade—do not re-enter impulsively.
- Time stop: if trade stagnates for two full rotations/periods (e.g., 2×5-min bars without progress), exit at market.
- News spike in your favor? Take 70–100% off; do not let a gift turn into a grind.
Playbook Setups He Repeats (fewer patterns, deeper reps)
He focuses on a small basket of patterns across markets so execution feels automatic. Mastery comes from depth, not breadth.
- ORB + Retest: opening range break with a clean pullback to the range edge; confirm with volume expansion.
- VWAP Reversion: extension 1.5–2.0× from VWAP into HTF level; fade back to VWAP with a tight stop beyond the extreme.
- Trend Continuation: pullback to rising/falling 20EMA aligned with HTF bias; enter on rejection close.
- Prior Day High/Low Sweep: liquidity sweep beyond PDH/PDL, swift reclaim, then continuation back into prior value.
- News Decompression: fade over-reaction after the first impulse if structure and liquidity support a mean reversion—size reduced.
Session Discipline & Market Selection (where he plays, when he plays)
Michael picks his battles. He favors liquid sessions and instruments where slippage and fills are predictable, and he respects his focus windows.
- Primary windows: first 90 minutes of the cash session and last 60 minutes; mid-day = maintenance only.
- Only trade instruments with consistent spreads and depth during your session; rotate out when liquidity vanishes.
- Weekly, choose 2–3 instruments to focus on; no more than 5 open watchlist setups per day.
- If you break session rules twice in a week, next week’s risk per trade drops by 50%.
- Friday rule: no fresh positions 30 minutes before close unless managing a proven high-win setup.
Data, Journal, and Review (turn reps into edge)
He journals like a coach. The goal is to capture cause → effect so you can prune what doesn’t pay and double down on what does.
- Record for each trade: setup tag, R planned, R realized, reason to exit, emotional state (1–5), and rule compliance (Y/N).
- Weekly review: filter by setup tag; drop any pattern with <1.3 expectancy over 30 occurrences.
- Build a “Do More” list (top two tags by expectancy) and a “Do Less” list (bottom two).
- Screenshot entries/exits with HTF context; annotate mistakes in plain English.
- If a rule is broken, write the future-tense fix (e.g., “Next time I will…”); then add a checklist item.
Prop-Firm Evaluation Protocol (pass with process, not luck)
He approaches evaluations like a professional risk test, not a lottery. The objective is variance control and steady R collection.
- Daily loss limit (firm’s DDL) ÷ 2 = your personal DDL; never touch the firm’s red line.
- Trade count cap: 1–3 high-grade trades per day; avoid over-trading to “hit target faster.”
- Risk ladder: start at 0.25% per trade; only step to 0.35% after +5R buffer is banked.
- News lock: no entries 5 minutes before high-impact releases unless the strategy is built for it.
- Hit the target early? Reduce size to 0.1% and protect the account—no heroics.
Psychology & Behavior Rules (be the thermostat, not the thermometer)
Michael systemizes behavior so emotions have less surface area. These constraints keep you executing like a pro even on rough days.
- Two losers in a row? Mandatory 20-minute break and a checklist reset.
- If you feel FOMO, write the missed setup rules and wait for the next valid trigger—no revenge trades.
- Use a visible timer to enforce “sit out” periods after big wins or losses.
- Speak your stop and target aloud before entry; if you can’t, you’re not ready.
- End the day when you hit +2R or −1.5R; consistency beats maximizing.
Portfolio & Correlation Control (one idea, one risk)
He avoids stacking correlated bets that secretly multiply exposure. Treat correlation like leverage in disguise.
- Do not hold more than one trade expressing the same macro idea (e.g., short risk via two indices).
- If you must stack, cut per-position risk so combined idea risk ≤ your per-trade cap.
- Avoid simultaneous trades in instruments with >0.7 rolling correlation over 20 days.
- When correlation spikes intraday (news), flatten the weaker position and keep the cleaner chart.
- If a runner is active, reduce the size of any new trade by 50% until the runner finishes.
Execution Checklist (the last screen before clicking)
Before committing capital, Michael runs a tight checklist that prevents avoidable errors. Use this as your pre-trade gate.
- HTF bias aligned? (Yes/No)
- Set up tag and grade ≥8/10? (Yes/No)
- Defined stop distance in R and in price? (Yes/No)
- Position size computed from risk% and ATR? (Yes/No)
- Three exit points planned (1R/2R/runner) and written? (Yes/No)
- News window clear or sized down? (Yes/No)
- Order type correct and hard stop attached? (Yes/No)
- Screenshot pre-trade taken? (Yes/No)
Scaling & Adaptation (grow size the boring way)
He increases risk only when the data says the edge is stable. This keeps growth smooth and drawdowns survivable.
- Step up size after a 30-trade sample with expectancy >1.3 and drawdown <3R.
- On any 5R drawdown from equity peak, cut size by 50% until back to peak +1R.
- Re-certify each setup quarterly: re-test rules, confirm edge, or retire it.
- Add one new setup at a time; require a forward-test of 20 occurrences before sizing normally.
- Keep a “kill switch” metric: three rule breaks in a session = day over, no exceptions.
Alejandro Perez Playbook & Strategy: How He Actually Trades
Core Philosophy (why his edge survives regime shifts)
Alejandro Perez builds strategies that don’t rely on one perfect market. He prioritizes repeatable rules and risk math over prediction so the process holds up when volatility expands or compresses. This section gives you the non-negotiables he uses before any entry signal matters.
- Define account risk per trade at 0.25%–0.5%; default to 0.25% when markets are erratic.
- Pre-set a max daily loss at 1.5R–2R; stop trading the moment it’s hit.
- Only trade setups that can deliver ≥2R realistic reward; skip everything else.
- Every order is paired with a hard stop at entry—no exceptions.
- Break any rule twice in a session? Shut down for the day.
Markets, Sessions, and Timeframes (where the probabilities live)
He prefers liquid instruments and hours where spreads stay tight and slippage is predictable. Timeframes are stacked, so higher-timeframe structure guides lower-timeframe execution. Use this map to pick battles you can actually win.
- Trade liquid majors/indices during their primary sessions; avoid thin, off-hours conditions.
- Anchor bias on HTF (4H/D1); execute on 5–15m for momentum or 30–60m for swings.
- If the spread widens beyond your backtested average by 50%+, reduce size by half or skip.
- Limit active watchlist to 3–5 symbols; more symbols usually means worse focus.
- No fresh positions in the last 30 minutes of your session unless managing a runner.
Strategy Architecture (simple rules, measurable edge)
Alejandro favors modular systems—entry, filter, exit, and risk are separate blocks you can test and improve independently. This makes your strategy easier to maintain and scale without rewriting everything.
- Use a directional filter (HTF structure/VWAP slope) to allow or disallow longs/shorts.
- Define one primary entry concept (break-retest or pullback-rejection); avoid mixing.
- Set stops mechanically (ATR or recent swing) and targets by structure or fixed R.
- Encode session/time filters: trade only during your “green” windows.
- One change at a time in optimization; re-test on out-of-sample before going live.
Entry Triggers (let price prove it)
Entries confirm your thesis at logical locations; the goal is to avoid guessing tops or bottoms. Alejandro waits for the market to “invite him in” with a clean, testable signal.
- Break-Retest: mark level; place stop order above/below after a retest and close back through.
- Pullback-Rejection: enter on the close of a rejection candle into the HTF level or VWAP band.
- Momentum Add-On: after +1R open profit, add 0.5x initial size on next valid trigger only.
- Skip signals forming >3× ATR away from the intended stop—location is compromised.
- No market orders on hesitation; use limit/stop orders tied to the trigger rules.
Volatility-Based Sizing (size follows risk, not feelings)
He keeps position sizing dynamic so every trade risks the same slice of equity regardless of volatility. This equalizes outcomes and tames drawdowns.
- Compute stop distance using ATR: stop = 0.8–1.2× ATR of the execution timeframe.
- Units = (Account × Risk%) ÷ Stop Distance; round down to nearest lot/contract.
- When realized volatility sits in its 75th percentile or higher, cut risk per trade by 30–50%.
- During major news windows, pre-define “trade or no-trade”; if trading, halve risk.
- Never increase size to recover losses; size only increases after a 20–30 trade green sample and a new equity high.
Trade Management & Exits (pay yourself, then let it run)
His exits are scripted before entry—partial profit funds the trade, while a runner compounds the good days. Treat time as a factor: if the market doesn’t move, cash the chips.
- Take PT1 at +1R (25–40% off); move stop to breakeven after a strong close beyond entry.
- Take PT2 at +2R; trail the remainder behind structure or a multiple of ATR.
- Time stop: if price stalls for two full rotations (e.g., two 5m swings) without progress, exit.
- If price tags +2R then gives a reversal close back inside the structure, flatten the remainder.
- Never flip directions immediately after an exit; wait for a fresh, fully valid setup.
Playbook Setups (fewer patterns, deeper reps)
Alejandro keeps a tight roster of patterns so execution becomes second nature. Mastery of a few pays more than dabbling in many.
- Opening Range Break + Retest: trade only if the range is compact and volume expands on break.
- VWAP Reversion: fade stretched moves back to VWAP at HTF levels; stop beyond extreme.
- Trend Continuation: pullback to 20EMA aligned with HTF bias; confirm with rejection close.
- Liquidity Sweep Reclaim: wick beyond prior high/low, swift reclaim, enter with stop under/over the sweep.
- Session High/Low Failure: late session failure at extremes; scale down risk and target mean.
Automation Pipeline (from idea to live)
His workflow moves from idea → rules → backtest → forward test → live with reduced size. Guardrails at each stage prevent survivorship bias and over-fitting.
- Backtest on multiple years and regimes; keep parameters coarse to avoid curve-fit.
- Forward test on a small live account/VPS for 4–8 weeks; log slippage and rejects.
- Deploy with 25–50% of the intended size for the first 20–30 trades; scale only if metrics hold.
- Monitor execution errors daily (missed orders, rejects, partial fills) and fix immediately.
- Keep an “abort switch”: shut down the bot if drawdown >5R from its forward-test baseline.
Monitoring & Maintenance (own the boring stuff)
Most edges die from neglect, not bad ideas. Alejandro schedules weekly and monthly reviews so drift and decay don’t creep in unnoticed.
- Weekly: export logs, tag setups, and update expectancy (avg R, win%, PF).
- Retire or pause any tag with expectancy <1.2 over the last 30 occurrences.
- Refresh regime filters quarterly (volatility bands, session behavior, spread averages).
- Keep a change log; only one parameter change live per week.
- Maintain a sandbox for new ideas—never test in production.
Drawdown Protocol (protect the engine)
He expects drawdowns and plans for them. The protocol reduces risk, simplifies decision-making, and speeds recovery without gambling.
- At −3R from equity high: cut size by 30%; trade only A-grade setups.
- At −5R: cut size by 50%; remove all add-ons; no trading during news hours.
- After two green days or +3R net, step risk up one notch; otherwise, hold reduced risk.
- If rule breaks occur during drawdown, pause one full session and review.
- Resume normal size only at a new equity high +1R.
Prop-Firm & Capital Constraints (pass with process)
Targets and drawdown rules change how you should attack the objective. Alejandro treats these accounts like a variance test, not a jackpot.
- Personal DDL = 50% of the firm’s daily loss limit; never approach the hard stop.
- Cap trades at 1–3 per day; no compounding size until target buffer ≥3R.
- Avoid news unless the strategy is built for it; if trading, risk ≤0.15% per position.
- If you hit 70–80% of the target early, cut size to 0.1% and protect the pass.
- No new trades after a red day that tags your personal DDL.
Psychology & Behavior (systems reduce emotion)
Alejandro engineers behavior into the rules so emotions have less room to sabotage execution. Use these constraints to keep your cool.
- Two consecutive losses → 20-minute break and checklist reset before any new trade.
- Speak the plan aloud (entry, stop, targets) before placing the order; if you can’t, skip.
- Use a visible timer to enforce “sit out” periods after big wins/losses.
- No social feeds or chat during your session; review them only after the trading window.
- End day at +2R or −1.5R—consistency beats maximizing.
Execution Checklist (the last gate before risk)
A good checklist catches avoidable mistakes. Run this quickly before you click.
- HTF bias confirmed and matches allowed direction?
- Set up tag graded ≥8/10 with all filters green?
- Stop distance measured (price and R) and size computed from risk%?
- Three exits planned (1R/2R/runner) and written down?
- News window clear or risk reduced per plan?
- Order type correct and hard stop attached at entry?
- Screenshot taken for the journal?
Start With Risk: Set per-trade size and daily loss limits.
Michael Toma says the first decision isn’t the entry—it’s the max you’re willing to lose today and on this trade. Locking in a per-trade risk (think 0.25%–0.5% of equity) and a hard daily loss limit forces discipline when emotions start flaring. With those numbers fixed, your size and stop become math, not a mood, and you instantly avoid the “just one more” spiral after a red start. Toma’s point is simple: if the ceiling is defined before the bell, the floor never drops out from under you.
Alejandro Perez backs it up by tying risk to volatility, so the same rule works in quiet and chaotic markets. He frames the day with a non-negotiable daily loss stop, then sizes each position to a small, consistent R so multiple attempts don’t wreck the account. If spreads widen or the chart turns jumpy, he halves the size instead of widening stops, keeping losses small and predictable. Implement both approaches together, and you’ll trade fewer “hope” setups, survive the outlier days, and keep your playbook intact long enough for the edge to show up.
Let Volatility Decide Size: Use ATR and cut risk in storms.
Michael Toma treats volatility like a throttle: when markets speed up, your position size should slow down. He translates noise into numbers with ATR, setting stops at roughly one ATR of the execution timeframe and sizing so the dollar risk per trade stays constant. If ATR expands, the stop widens and the number of shares or contracts shrinks automatically. That way, a wild session doesn’t secretly multiply your exposure.
Alejandro Perez adds a regime layer by checking recent volatility percentiles and cutting risk 30–50% when the reading sits in the top quartile. He also watches spread behavior; if spreads widen far beyond normal, he reduces the size or skips the trade rather than pushing stops wider. During scheduled news, he halves the risk unless the setup specifically benefits from the event. Together, Toma’s ATR math and Perez’s regime filter keep losses small, exits honest, and the equity curve smoother when markets get loud.
Trade A+ Setups Only: Grade entries and require a two-to-one reward
Michael Toma argues that most drawdowns come from average setups, not bad luck, so he grades every trade before risking a dollar. He keeps it simple: trend alignment, clean level, liquidity, and room to at least 2R—score it and only pull the trigger if it lands in “A” territory. If a setup scores lower, it goes to the journal, not the order ticket, because protecting attention is as important as protecting capital. He also insists on session filters; an A+ during your high-focus window beats a B+ after-hours every time. By front-loading discipline like this, Toma makes the pass his default and the trade the exception.
Alejandro Perez echoes the same idea but adds a location rule: the trigger must happen where the chart says it should, not where emotions want it. He wants a higher-timeframe confluence and a structure-defined stop that keeps the math honest, then a realistic 2:1 or better target before entry. If volatility pushes the entry too far from the stop, he downgrades the grade and walks away—no chasing, no “I’ll tighten later.” Used together, Toma’s grading and Perez’s location discipline turn “maybe” trades into clean yes-or-no decisions that compound consistency over time.
Diversify By Strategy, Duration, And Underlying To Control Drawdowns
Michael Toma frames diversification as risk engineering, not just owning “more stuff.” He splits exposure by playbook type—trend continuation, mean reversion, and breakout—so one bad day in a single behavior doesn’t sink the boat. He then staggers holding periods, pairing quick intraday rotations with slower swing positions, which smooths the equity line when a session theme dries up. Finally, he avoids doubling the same macro bet, so a short index and a short high-beta stock aren’t counted as two independent trades. By designing variety across strategy, duration, and underlying, Toma reduces correlation shocks and keeps losses linear instead of exponential.
Alejandro Perez takes it further by assigning risk budgets to each bucket and refusing to let any one sleeve exceed its cap. If a mean-reversion system hits a cold streak, he automatically routes more “tickets” to trend setups without increasing total account risk. He also rotates symbols based on changing liquidity and volatility, swapping a sleepy pair or index for another instrument that fits the same strategy better. Across the week, Perez wants different edges firing at different times, so the equity curve keeps climbing even when one module stalls. The combined approach forces discipline: diversify with intent, size by bucket, and treat correlation like hidden leverage.
Process Over Prediction: Script entries, exits, and review every week
Michael Toma keeps the crystal ball on the shelf and doubles down on scripts. He writes the entry, stops, and profit targets before clicking—then lets the trade either qualify or die on the checklist. That removes improvisation, which is just a fancy word for breaking rules when money is on the line. Toma’s mantra is simple: the strategy decides; the trader executes. When a trade is closed, he tags it by setup, session, and volatility so the data can tell him which plays deserve more capital.
Alejandro Perez runs the same play but adds a tight review cadence. Every week, he filters results by setup and expectancy, promotes the top two patterns, and demotes anything that slips below a minimum threshold. He also runs a quick “post-mortem” on rule breaks, rewriting a one-line fix he’ll see next session on his checklist. Perez treats the journal like a lab notebook—evidence first, opinions later—so edge compounds through small, boring improvements. Follow the pair’s approach, and the wins come from process math, not predictions you hoped would be right.
The through-line from Michael Toma and Alejandro Perez is simple: edge survives when risk comes first, effort stays consistent, and execution is systemized. Toma’s lane is enterprise-level risk—getting traders from A to B with structure—while Perez turns robust ideas into rule-driven automation that removes hesitation and revenge trades from the loop. Together, they underscore that most traders have enough knowledge; what separates outcomes is disciplined work and a framework that keeps you inside guardrails even when life or markets get loud.
They push a practical risk playbook: define daily loss limits, size by volatility, and diversify by strategy and duration so one behavior doesn’t sink the book. Toma models that in real time—an S&P-focused futures trader whose best performers this year came from bonds and crypto, a reminder to follow opportunity rather than prediction. When personal stress or overconfidence shows up, the fix isn’t a new setup; it’s a smaller size, mentoring, and patience.
Perez shows how to encode market structure into algos and then keep them alive: treat systems as evolving, review and tweak on a schedule, and let the machine execute the rules you already trust. Automation isn’t a “plug-and-profit” shortcut—it’s a disciplined way to enforce your edge, especially under prop-firm constraints where rule compliance and variance control matter more than hero trades. The prop world itself is shifting toward saner rules; use it as Stage One funding, build a track record, and graduate to more durable capital once your process proves itself.
