Table of Contents
Michael Melissinos is the guest in this interview—a long-term, diversified trend-following trader who launched young, raised outside capital, and now runs money for dozens of investors. Recorded on the Desire To Trade podcast, this chat digs into why Michael matters to everyday traders: he strips the mystique out of systematic trading, emphasizes survival over hype, and shows how a calm, rules-driven process can scale from personal accounts to a professional fund.
In this piece, you’ll learn Michael’s core approach—long-term breakouts and moving-average signals across global futures, held for months, with simple daily end-of-day execution—and how he sizes risk, sets stops, and keeps the portfolio diversified without overloading on correlated markets. You’ll also see his playbook for transparency with investors, the fee logic that supports long relationships, and the mindset that keeps him steady through dry spells and drawdowns. If you want a clear, beginner-friendly model for building—or just borrowing—a durable trend-following process, Michael Melissinos lays out the blueprint here.
Michael Melissinos Playbook & Strategy: How He Actually Trades
Core philosophy: survive first, let trends do the heavy lifting
Trend following works because it aligns with major moves without needing to predict them. Michael Melissinos keeps the method simple on purpose, so it scales from a single account to a full portfolio and stays robust when markets get weird.
- Trade rules, not opinions; no discretionary overrides once a signal is live
- Grade every idea by “will this keep me alive in a 30–40% drawdown?”
- Accept that most trades are small losses; the job is to stick around for the monster.s
- Evaluate edge across decades and regimes, not months
- If a tweak adds complexity without improving survivability, drop it
Markets he trades and why diversification matters
The engine is a diversified set of liquid global futures, so no single market can make or break the year. Breadth reduces reliance on being “right” about equities and lets strong trends elsewhere pay the bills.
- Focus on liquid futures: equity indices, rates, FX, metals, energies, ags, softs
- Aim for 40–70 markets when possible; a minimum of one per major sector
- Replace thin or structurally compromised contracts with better proxies
- Roll rules are standardized and automated (no ad-hoc roll timing)
- Cap sector exposure so one theme (e.g., energies) can’t dominate portfolio risk
Signal generation: simple breakouts and moving averages
Signals are deliberately plain. Breakouts capture regime shifts; moving averages filter noise. You don’t need exotic indicators—consistency beats clever.
- Long entry: daily close breaks above the 100–200 day high (choose and fix one)
- Short entry: daily close breaks below the 100–200 day low
- MA filter: only take longs when price > 200-day SMA and shorts when price < 200-day SMA
- No anticipatory entries; signals only on confirmed closes
- One market = one position per direction; no stacking multiple independent entries
Position sizing: volatility-normalized risk per trade
Every position is scaled to risk the same fraction of equity, so a Swiss franc doesn’t dwarf soybean oil just because it’s jumpier. Volatility sizing keeps losers small and winners meaningful.
- Define account risk per trade: 0.25%–0.50% of equity (pick one and stick to it)
- Use 20-day ATR (or true range proxy) for volatility units
- Contracts = floor( (risk_per_trade × equity) / (ATR × dollar_value_per_point) )
- Recompute size at entry only; do not “top up” during adverse moves
- If equity drops 20% from peak, reduce risk_per_trade by 25% until recovery
Stops and exits: cut quick, trail slow
The edge is asymmetric exits—small predefined losses and open-ended gains. Trailing logic keeps you on the ride without trying to call tops.
- Initial stop = entry price −/+ (2.0–3.0) × ATR (opposite for shorts)
- Trail stop at (3.0–4.0) × ATR from the highest/lowest close since entry
- Time stop: if trade hasn’t moved ≥ +1 ATR after 40 trading days, exit at market
- Exit and reverse on opposite breakout when system rules say so
- Never widen a stop; only move it in the direction of the trend
Portfolio construction and correlation controls
Great trend systems can still blow up if you stack the same theme five ways. Control correlation so the book behaves like many independent bets.
- Group markets into sectors; cap live risk to ≤ 25% of total across any one sector
- If two markets’ 90-day returns correlate > 0.8, allow only the higher-quality signal
- Cap aggregate active risk (sum of position risks) to ≤ 10% of equity
- Use volatility parity at the position level; no “conviction” overrides
- If > 50% of portfolio risk depends on USD direction, cut weakest USD-linked positions
Daily workflow: end-of-day, rules-first execution
The process is calm and repeatable. End-of-day execution avoids overtrading and frees the system from intraday noise.
- Update prices, compute signals, and size new trades after the official settlement.
- Place stops/targets as resting orders; avoid market-on-open unless liquidity is thin.
- If slippage > 1 ATR unit on entry, reduce size by 50% and reassess liquidity.y
- No intraday “checking” unless for operational issues (rolls, halts, limits)
- Log fills, slippage, and any exceptions are immediately
Drawdown playbook: predefined brakes and resets
Drawdowns are part of the model. The key is knowing exactly how you’ll respond so you don’t improvise when it hurts.
- At −10% from high water mark (HWM): no changes; review execution quality
- At −20% from HWM: reduce risk_per_trade by 25%; freeze any new system tweaks
- At −30% from HWM: reduce risk_per_trade by 50%; re-validate data/rolls/slippage
- At −40% from HWM: pause new entries for 10 trading days; continue to manage exits
- Resume prior risk only after closing equity makes a new HWM
Capital growth, fees, and account hygiene
Compounding works when the process is clean—fees aligned, cash efficiently used, and no sloppy leaks. Keep the book tight so trends accrue to you, not to friction.
- Recalculate position sizes monthly using end-of-month equity (not daily)
- Keep idle cash in safe, short-duration instruments; never reach for yield
- Target commission + fees ≤ 1% of equity annually at your turnover rate
- If annual turnover rises > 2× your historical median, investigate slippage sources
- Maintain a minimum cash buffer for margin calls equal to 5–8× average daily variation margin
Research discipline: controlled change, robust testing
Change is allowed—reckless tinkering isn’t. Test slowly, across regimes, and only ship improvements that clearly strengthen robustness.
- Test any new rule on at least 20 years of data across all sectors you trade.
- Use a walk-forward or expanding window; avoid optimizing to a single era
- Approve a change only if it improves both the CAGR-to-stagnation ratio and the max DD
- Limit production changes to one per quarter; parallel run new logic in paper for 90 days
- Keep a kill-switch metric: if live tracking error vs. backtest exceeds a set band, revert
Mindset and investor communication
A rules-based process still needs a human who stays steady and transparent. Communicate the plan upfront so nobody is surprised when the system behaves exactly as designed.
- Publish the ranges you operate within (lookback windows, ATR multiples, risk per trade)
- Pre-brief stakeholders that win rates can sit near 35–45% and that long flat periods happen.
- Report monthly with the same template: performance, risk, notable trends, slippage, and any rule change.s
- Say “I don’t know” about forecasts; reiterate what the system will do next, not what markets will do
- Keep your personal account on the same ru, lest so incentives are aligned
Size Every Position by Volatility, Not Conviction or RecP&L P&L
Michael Melissinos stresses that position size is math, not emotion. Volatility tells you how loud a market speaks, so you let ATR or similar measures set your risk instead of gut feel. Pick a fixed risk-per-trade—say 0.25%–0.50% of equity—and translate that into contracts using current volatility, not yesterday’s win or loss. This keeps a choppy currency from overpowering a steady bond future just because it’s moving more.
Conviction and recent P&L are terrible sizing inputs because they spike and crash with mood. Melissinos keeps size consistent at entry and lets the stop and trailing logic handle the rest, avoiding “top-ups” during drawdowns. If equity pulls back significantly, he dials down the risk-per-trade mechanically until the account recovers. The result is uniformly small losses across markets and clean exposure when a real trend finally runs.
Diversify Across Markets, Sectors, and Timeframes to Reduce Portfolio Whiplash
Michael Melissinos points out that real diversification isn’t owning more tickers—it’s owning different sources of trend. Spread risk across equities, rates, FX, metals, energies, and ags so one theme can’t hijack your month. When crude is stuck, currencies or bonds might trend, and that mix smooths the equity curve. The goal is fewer boom-bust cycles and a steadier shot at catching something that’s actually moving.
He also diversifies across time by staggering lookbacks so signals don’t flip all at once. A blend of medium and longer breakout windows keeps you from getting whipsawed by a single regime. Melissinos caps sector risk, limits highly correlated positions, and keeps total active risk inside a defined band. That way, a synchronized move in one narrative can’t torpedo the whole book.
Trade Simple Breakout Rules; Skip Predictions, Opinions, and Intraday Noise
Michael Melissinos keeps entries brutally simple: buy strength on confirmed breakouts, sell weakness on breakdowns, and ignore everything that isn’t a rule. He waits for daily closes, not tick-by-tick wiggles, so false starts and intraday head-fakes don’t push him around. No front-running, no “I think it’ll break tomorrow,” just act when the signal is real. That clarity cuts hesitation and makes execution repeatable when emotions spike.
He also filters trades with a long-term trend gauge, so he’s only buying above the major trend and shorting below it. Predictions and narratives get zero weight because they don’t improve the distribution of outcomes; sticking to the breakout does. Melissinos emphasizes that most signals will be small losses, and that’s fine—the handful of outsized trends pays for the rest. The job is to show up for those outliers, and simple breakout rules keep you there without second-guessing.
Define Risk Upfront With ATR Stops, Trail Winners Without Second-Guessing
Michael Melissinos starts every trade by fixing the loss he can live with before he hits buy. Using a multiple of ATR, he places the initial stop where normal noise won’t tag it, but real trend failure will. That predefined exit turns uncertainty into a known cost and prevents “I’ll just give it more room” drift. Once the order is live, the stop is the boss—no widening, no negotiating.
As price moves, Melissinos trails the stop at a looser ATR multiple so he can ride the move without trying to nail the top. The trailing stop only ratchets in the direction of profit, allowing winners to breathe while locking in progress. If momentum stalls for too long, a time-based exit clears the slot for a fresher signal. The combination—fixed initial risk, one-way trailing, and occasional time-outs—keeps losers small and lets the rare monster trend write the P&L.
Control Correlation; Cap Sector Exposure And Total Active Book Risk
Michael Melissinos treats correlation like hidden leverage—if everything moves together, your real risk is bigger than it looks. He groups markets by sector, caps how much risk any one theme can carry, and cuts the weaker signals when correlations spike. That keeps a synchronized move in, say, energies or rates from flooding the book. He also watches aggregate active risk so total system exposure never drifts past a pre-set ceiling.
When trends cluster around a macro driver—like a strong dollar—Melissinos trims USD-linked positions until the book isn’t one bet in disguise. If a highly correlated pair lights up, he takes the cleaner signal and drops the duplicate to avoid stacking the same trade twice. The goal is a portfolio of many small, independent edges instead of one oversized narrative. Control correlation first, and the rest of the risk rules actually work.
In the end, Michael Melissinos shows that durable trading is just disciplined living applied to markets: rules over opinions, survival over excitement, and radical simplicity that still scales. He builds around long-term trend signals, sizes by volatility so every position risks the same fraction of equity, and defines exits before entry with ATR-based stops that only tighten in the direction of profit. Breadth matters—equities, rates, FX, metals, energies, ags—while correlation caps keep one macro theme from hijacking the book. He runs the process end-of-day, accepts small losses as the cost of admission, and lets a few monster trends write the P&L.
Just as important, Michael treats the human side like part of the system. He learned the cost of waiting for “more confidence” by missing a big 2010 move, so he favors shipping a clean rule set and letting time do the compounding. Dry spells and drawdowns are handled by predefined risk reductions, not ad-hoc tweaks, and he keeps perspective by stepping away (coaching, family, life) so markets can’t yank his decision-making around. With transparent communication—laying out the process in plain language—he aligns expectations and reduces the urge to predict. The takeaway is simple: codify the mechanics, constrain risk, diversify intelligently, and give trends the time they need to pay you.
