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Today’s interview features Troy Bombardia—systematic trader, researcher, and founder of Bull Markets—diving into why he ditched pure chart-reading for quantified, rules-based models. Recorded in Sydney, Troy walks through his evolution from 2008’s wild bank shorts and the silver boom to building a family-run hedge fund approach that tests ideas across decades, not months. He’s blunt about the limits of discretionary calls and why fundamentals, valuations, and technicals must work together inside a repeatable process for any trader who actually wants a durable edge.
In this piece, you’ll learn Troy’s system-first blueprint: start simple, backtest far into history, avoid overfitting, and layer fundamentals and valuations before short-term signals. We’ll cover how he quantifies “money flow” in FX, why a 200-day filter can tame downside while leverage works for you—not against you—and the traps that kill most strategies (too many indicators, too little data, and belief-driven tinkering). If you want a practical, beginner-friendly map to build a robust trading model—one you can actually follow—this is it, straight from Troy Bombardia’s playbook.
Troy Bombardia Playbook & Strategy: How He Actually Trades
Core philosophy: rules first, opinions last
Troy’s edge comes from quantified rules that survive decades of history, not a week of anecdotes. The goal is simple: build systems that keep you in sync with major flows and out of chop.
- Build every idea into a rule you can code or a checklist.
- Require out-of-sample and long lookback validation before live use.
- Favor robustness over precision: fewer moving parts, fewer parameters.
- Separate research (ideas) from execution (signals); never mix the two mid-trade.
Markets and instruments he focuses on
He concentrates on liquid index futures, major FX pairs, and large-cap equities/ETFs where slippage is low and data is clean. That lets the rules speak without getting distorted by illiquidity.
- Trade liquid benchmarks: S&P 500/Nasdaq futures or ETFs, G10 FX, and top-tier index/sector ETFs.
- Avoid thin names; set minimum ADV and tight spread thresholds.
- For equities, screen to mega/large caps; for FX, stick to majors and gold.
- Use centralized products for clarity (index futures over single stock options when testing core ideas).
Signal framework: trend, mean reversion, and regime
The backbone is regime awareness: what works in uptrends often fails in bear or high-vol regimes. He blends slow trend filters with simple, durable entry cues.
- Define regime with a slow filter (e.g., price above/below a 200-day or a multi-month Donchian).
- Only take long signals in uptrend regimes; allow tactical shorts or stay flat in downtrends.
- Use 1–2 primary entry families per system: breakout continuation or oversold mean-reversion.
- Cap indicators at 2–3 total; if you need more, the edge isn’t real.
Breakout continuation entries
When higher timeframes are driving, he wants to join strength rather than predict reversals. The key is clean break logic plus risk that scales with volatility.
- Entry: buy on a new 3–4 week high that clears prior resistance by a fixed buffer (e.g., 0.25–0.5 ATR).
- Confirm with breadth or relative strength vs a baseline (index > 20-day RS percentile).
- Skip trades if the breakout occurs into scheduled high-impact risk events (define a “no-trade window”).
- Size by ATR so position risk stays constant across regimes.
Mean-reversion entries (equities focus)
Equities often snap back after fast selloffs within larger uptrends. He exploits that with simple pullback rules.
- Only act when the slow regime filter is bullish.
- Entry: buy when close < lower Bollinger band (20,2) AND 2–3 day RSI < 20.
- Add a second-day trigger: enter on the next up-close to reduce knife-catching.
- Hard fail condition: no entry if the 20-day average is sloping down for 10+ sessions.
Fundamental and valuation overlay (lightweight)
Troy favors signals first, but he’ll tilt exposure using broad valuation and macro context to avoid obvious traps. Keep it lightweight and rules-based.
- Reduce gross exposure when the equity risk premium is compressed or forward multiples are in the top decile of your history.
- In FX, favor carry-aligned pairs when signals are mixed; stand down when carry and signal disagree strongly.
- Use binary toggles (on/off or +/– 25% gross) rather than subjective overrides.
Risk sizing and leverage
Survivability beats brilliance. Vol-scaled sizing and predefined loss limits keep the system tradable under stress.
- Risk a fixed fraction of equity per trade (e.g., 0.25–0.5%).
- Convert that risk into units via ATR or recent true range.
- Cap portfolio-level daily loss (e.g., –1.5%) and weekly loss (e.g., –3%); if hit, stop trading until next period.
- Use modest leverage only when portfolio volatility is below target; auto-de-leverage when realized vol spikes.
Portfolio construction and diversification
He diversifies by return drivers: trend vs mean reversion, equity vs FX, short vs medium timeframe. The goal is smoother equity curves without diluting the edge.
- Run 2–4 uncorrelated systems simultaneously.
- Limit correlated positions: max 2 signals pointing the same way in highly correlated indices.
- Target portfolio vol (e.g., 10–12% annualized) and scale all systems to hit it.
- Set per-market risk caps (e.g., max 30% of portfolio risk in any single index future).
Trade management and exits
Entries get the glory, exits do the heavy lifting. Troy prefers blunt, proven exit rules that don’t curve-fit.
- For breakouts: initial stop = 1.5–2 ATR; trail behind a short moving average or a 10-day low.
- For mean reversion: exit on return to the 20-day average or a fixed profit multiple (e.g., +1.2–1.5R).
- Add time stops: if trade hasn’t moved after X bars (e.g., 10 sessions), reduce or exit.
- Never widen stops; only tighten per rules.
Handling volatility and news
Volatility is both risk and opportunity. He adapts size and selectivity as ranges expand to avoid getting chopped up.
- Halve size when realized 20-day vol exceeds a top-quartile threshold.
- Require cleaner structures (larger buffers) in high-vol regimes.
- Institute event risk rules: flat or reduced size into pre-defined macro releases for FX and indices.
- If slippage > planned by 2x on entry, cut size on the next trade in that instrument.
Execution: simple, reliable, repeatable
Edge dies in sloppy execution. He keeps routing, timing, and order types standardized to reduce variability.
- Use limit-at-touch or market-on-close/market-on-open depending on system design; don’t mix.
- Pre-compute orders and upload before session; no ad-hoc tinkering intraday.
- Track slippage per instrument; if it trends worse for a month, downgrade or replace that venue.
- Automate alerts; manual steps should be checklist-driven.
Data hygiene and testing
Clean data and honest tests prevent fantasy P&Ls. Troy emphasizes durability over perfect backtests.
- Use long samples (20+ years for indices/FX where possible).
- Include realistic transaction costs and slippage in all tests.
- Walk-forward or k-fold style validation; ban peeking and indicator look-ahead.
- Reject systems whose edge vanishes after tiny parameter nudges.
Review cadence and metrics.
He runs a tight feedback loop that separates luck from process. The focus is on risk metrics and behavior under stress.
- Weekly: review open positions, regime flags, realized vs target vol, and rule compliance.
- Monthly: analyze win/loss distributions, average R, and contribution by system and market.
- Quarterly: decompose drawdowns by regime; prune or refit only if edge degrades across multiple windows.
- Maintain a rule-breach log; any breach triggers a size reduction next week.
Psychology and discipline
Rules are only as strong as the trader holding them. Troy designs the process to make the correct action the easy action.
- Pre-commit to max daily screens/time; no doom-scrolling charts.
- Use “if-then” scripts for pain points (e.g., “If I want to move a stop, then I close the platform and re-read the rule”).
- Keep the size small enough that a 5-trade losing streak is emotionally tolerable.
- Measure process compliance; reward perfect execution, not P&L.
Common mistakes he avoids
Most traders fail by adding noise or fighting regimes. He cuts these errors off at the source with structural rules.
- No discretionary overrides after entry.
- No indicator stacking beyond 2–3 inputs.
- No counter-trend trades without explicit mean-reversion rules and a regime filter.
- No strategy changes inside a drawdown; only after the scheduled review with data.
A sample daily/weekly routine
Consistency compounds. Here’s how he keeps the machine running without burning out.
- Pre-open: update signals, verify data, set orders, recompute sizes against current ATR and risk caps.
- Mid-session: no chart-surfing; only act on alerts that match pre-planned rules.
- Close: reconcile fills, log slippage, export metrics.
- Weekend: re-run regime maps, sanity-check correlations, and rehearse “if-then” responses for the week ahead.
Size Each Trade by ATR to Keep Risk Constant Across Regimes
Troy Bombardia keeps risk steady by sizing positions with Average True Range, not gut feel. He first chooses a small fixed account risk per trade—think 0.25% to 0.5%—then converts that into units using ATR so each entry faces similar dollar volatility. This means a choppy, high-vol market earns a smaller position while a quiet, trending market allows a larger one. The result is smoother equity and fewer “all-in at the worst time” disasters.
To apply it, measure current ATR, set your stop distance in ATR terms, and back into quantity so a full stop equals your chosen percent risk. If ATR doubles next week, your position auto-shrinks; if ATR halves, it scales up without you overthinking. Troy Bombardia emphasizes that this rule travels well across assets—indices, FX, metals—because ATR normalizes volatility differences. It’s a small, mechanical tweak that makes your process more durable when markets flip regimes.
Use Slow Trend Filters To Define Regime Before Any Signal Fires
Troy Bombardia treats regime as the master switch—no regime, no trade. A slow filter like the 200-day moving average or a multi-month Donchian channel tells him whether markets are broadly rewarding longs or punishing them. When price sits above the filter, he allows long setups; when below, he either stays flat or switches to tactical shorts. This simple gate stops most rule breaks that happen when traders force signals in the wrong environment.
To apply it, pick one slow filter and commit for a full cycle before changing it. Map actions to states: “above = only long signals; below = no longs or short-only systems.” Add a slope or breadth confirmation if you want extra safety, but keep it minimal so you don’t curve-fit. Troy Bombardia stresses that a clean regime rule trims false positives, cuts time spent fighting chop, and makes every downstream decision easier.
Diversify By Underlying, Strategy, And Holding Duration To Smooth Equity
Troy Bombardia spreads risk across uncorrelated engines so one bad week doesn’t sink the ship. He mixes indices with majors in FX and a metals sleeve, so different macro drivers offset each other. On top of that, he runs both breakout continuation and mean-reversion systems, so the portfolio has edges in trends and chop. The final layer is time: some trades hold for days, others for weeks, preventing all P&L from hinging on one timeframe.
To mirror Troy Bombardia’s approach, cap any single asset class to a fixed share of portfolio risk and enforce a limit on highly correlated positions. Run at least two distinct rule sets—one for momentum, one for pullbacks—and size them so neither dominates realized volatility. Stagger average holding periods by design: a fast system harvesting short swings alongside a slower system riding regime moves. Rebalance risk quarterly so winners don’t bloat, and prune overlaps when correlation spikes, keeping the equity curve steady even as markets rotate.
Prioritize Mechanics Over Prediction: Simple Rules, Backtests, And Time Stops
Troy Bombardia doesn’t try to guess headlines; he hardwires actions into simple, testable rules. If a setup appears, the rule triggers; if it doesn’t, he does nothing. Backtests aren’t fortune tellers, but they reveal whether an idea survives many regimes without constant tinkering. This mechanical focus turns “I think” into “I do,” removing hesitation when markets get noisy.
He also uses time stops to kill trades that just sit and bleed attention. If the price hasn’t moved after a predefined window, Troy Bombardia exits and recycles risk into fresher signals. The same discipline applies to stop placement and profit taking—pre-set, not improvised mid-trade. With mechanics front and center, prediction becomes optional, and execution stays crisp even when emotions try to hijack the plan.
Prefer Defined Risk In Turbulence; De-Leverage High Variance, Undefined Risk
When markets get jumpy, Troy Bombardia shifts toward positions where the worst-case loss is known up front. That can mean using hard stops religiously in futures, or choosing defined-risk option structures instead of naked exposure when vol explodes. The goal is survival-first sizing, so a single gap or headline can’t nuke the account. If realized volatility spikes, he automatically cuts leverage rather than trying to “tough it out.”
Troy Bombardia also tightens his playbook around event windows and liquidity. He caps daily and weekly loss, trims position counts, and concentrates only on the cleanest signals until volatility normalizes. If variance stays elevated, he scales down targets and stretches buffers so noise doesn’t trigger unnecessary whipsaws. The theme is simple: define risk precisely, pay for protection if needed, and let de-leveraging keep you in the game long enough for your edge to reassert.
Troy Bombardia’s core lesson is brutally simple: build rules that survive history and then follow them without flinching. He moved away from opinion-led calls to system-led decisions because markets punish prediction but reward consistent mechanics. Use slow regime filters (think long moving averages or multi-month break structures) to decide when to play offense, and let volatility determine size so one trade never dominates the equity curve. Keep the toolset minimal, test ideas over long samples, and refuse to ship anything that only works with fragile parameters.
He also shows how a light fundamental and valuation overlay can keep you out of obviously asymmetric risk, especially at stretched multiples or when carry and momentum disagree in FX. In turbulence, define the downside up front, tighten event rules, and de-leverage until realized variance cools. Diversify by return driver—trend and mean reversion—across indices, majors in FX, and a metals or commodity sleeve, with staggered holding periods so different engines pay the bills at different times.
Finally, Troy Bombardia’s edge lives in process discipline: pre-compute orders, standardize execution, track slippage, and run a recurring review cadence that focuses on risk, behavior in drawdowns, and rule compliance—not storylines. When a trade stalls, time-stop it; when volatility jumps, size down automatically; when correlation spikes, prune overlaps. Do these unglamorous things consistently, and the strategy becomes what he actually trades: a durable, rules-first playbook that compounds through many regimes.
