Table of Contents
John Bannan sits down for a candid interview on building a durable trading career—why he shifted from stock picking to index futures, how he’s traded full-time since 2009, and what really improves during drawdowns. He explains his long-only bias on the S&P and Nasdaq, average holds of three to five days, and the “bear market filter” that keeps him out during dangerous stretches. You’ll also hear how sharing live signals for years sharpened his discipline and pushed him to keep iterating his system.
In this piece, you’ll learn the core of Bannan’s trader strategy: harvesting multi-day trends with simple, robust tools (ATR, moving averages), plus a cycles-based timing overlay to flag potential turning dates—always confirmed by price. We’ll unpack his approach to risk, how he handles inevitable slumps, and what changes when you manage outside capital versus your own account—so you can adapt these ideas to your playbook fast.
John Bannan Playbook & Strategy: How He Actually Trades
Core Philosophy: Iterate Through Drawdowns
When things are smooth, you don’t learn much; the real upgrades happen during slumps. John Bannan treats every drawdown as a sprint of research and iteration, so the system that exits the valley isn’t the same one that entered it.
- Treat any −8% to −12% equity dip as a “research sprint”: freeze new risk, review every trade, and document one concrete rule tweak before resuming full size.
- Keep a living “post-mortem log” with three fields per loss: the rule followed, the market condition, and the fix you’ll test next week.
- Resume risk in thirds (33% / 67% / 100%) only after five trades, confirm the tweak adds edge without breaking older edges.
Cycle-Timed, Price-Confirmed Entries
Bannan blends repeating market cycles with classic indicators. The cycle work gives him advance dates to watch; price action and simple math decide whether to act.
- Build a “turn-date calendar” 2–6 weeks out (from your cycle model). Use it only as a watchlist—never as a signal.
- On a turn date, go long only if the session closes above the 20-EMA and prints a higher high vs. the prior two days.
- Place a stop-limit entry for the next day at High + 0.20×ATR(14); cancel if not triggered the next session.
- Ignore any turn-date that doesn’t align with price—no confirmation, no trade.
Simple Math: ATR & Moving Averages Drive Risk
He keeps the math plain: ATR for distance, moving averages for regime. That simplicity makes the rules repeatable under pressure.
- Initial stop: 1.5×ATR(14) from entry; position size so 1R = 0.5%–1.0% of account.
- Trail once price advances 1.0R: move stop to entry; after 1.5R, trail at 1.0×ATR(14) beneath the close.
- Regime filter: trade full size only when 20-EMA > 50-SMA; if 20-EMA < 50-SMA, cut size by half or stand aside entirely.
- If ATR expands >30% above its 20-day average, reduce size by 33% to account for jumpy ranges.
Favor a Higher Win Rate Without Killing R: R
Early in his journey, he ran 50/50 systems with 2.5–3.0R winners. Today, he leans into a steadier hit rate while protecting payoff.
- First target at +1.5R (scale 50%); let the runner aim for 2.5–3.0R with the ATR trail.
- If price stalls for three consecutive closes within ±0.3×ATR of your entry, exit flat and recycle the setup.
- Cap daily new risk at 1.5R across all positions; never add new exposure if open risk already exceeds 2.0R.
- If three losers occur back-to-back in the same regime, pause that regime until a fresh 20/50 crossover re-confirms direction.
A Practical Bear-Cycle Filter
Experience through rough markets matters. When the higher-timeframe trend is hostile, he prioritizes defense and patience.
- No longs if the 50-SMA < 200-SMA and price is below the 20-EMA; only consider counter-trend probes at half size after a bullish outside day.
- After any 5% index slide in 10 sessions, require a follow-through day (close > prior high on >20-day median volume) before restoring full size.
- During bear conditions, widen stops to 2.0×ATR and cut target to 1.2–1.8R; the goal is survival and base hits, not home runs.
- Re-enable normal risk only after two weekly closes back above the 50-SMA.
Managing Other People’s Money (and Your Own)
Accountability sharpens discipline. Bannan runs with rules that protect capital and reputation first.
- Pre-declare a firm max drawdown (e.g., −12%); at −8% trigger “risk-off mode” (half size), and at −12% stop trading live for two weeks while you test fixes.
- Hard daily loss cap: stop for the day after 1.5R closed loss or two full-stop outs—whichever comes first.
- Publish (to yourself or stakeholders) a weekly scorecard: win rate, average R, expectancy, rule-break count; halt new risk the next week if any rule-break >0.
- Never average down. Add only if the trade has banked at least +1.0R and the new add follows the same entry rules as the original.
Multi-Day Hold Tactics
His plays aim to harvest a few days of trend, not minutes. That demands clear timing and unemotional exits.
- Time stop: exit on the fifth close after entry if the position hasn’t hit +1.0R.
- Strength add: after a strong close (>0.75×ATR above the 20-EMA) and your stop at breakeven, you may add 0.5× initial size with a fresh 1.5×ATR stop.
- If a gap opens ≥1.0×ATR against you and tags the stop at the open, do not re-enter until a new signal forms after two full sessions.
- Into strength, trail below the prior day’s low by 1.0×ATR once the trade is >2R.
Daily Routine & Tools That Make This Work
Edge compounds in routine. He combines prep, execution, and review so feedback is never delayed.
- Pre-market (20 minutes): mark today’s cycle watchlist, pre-compute ATR(14), and record 20-EMA/50-SMA regime; set conditional orders only—no market chasing.
- Mid-session (5 minutes, twice): check if any entries triggered; adjust stops mechanically—no discretion unless a trading halt occurs.
- End-of-day (15 minutes): export fills, tag each trade with regime, setup, and cycle-alignment; update expectancy by setup before bed.
- Weekly (45 minutes): re-opt nothing. Only remove rules that caused rule-breaks or add guardrails that reduce them.
Turn-Date Calendar: Building and Using It Correctly
Cycle analysis is a timing overlay, not a crystal ball. The calendar narrows attention so the simple rules can do their job.
- Generate candidate dates from your cycle model and publish them to a shared sheet; lock them weekly—no midweek edits.
- Tag each date with “up-bias,” “down-bias,” or “inflection” based on the composite cycle; trades still require price confirmation.
- If three consecutive tagged dates fail to produce valid price signals, lower the weight of that cycle component by 25% for the next month.
- Never hold a trade because a turn-date is “due.” Exits are dictated by ATR trails, time stops, and targets—period.
Position Sizing for Sanity
Sizing is where careers are made or broken. Keep it small enough to let the math work.
- Use: Position = (Account × 0.75% risk) ÷ (1.5×ATR(14)). Round down to the nearest contract/share lot.
- If portfolio open risk >2.0R, reject new signals automatically—even perfect ones.
- After a green week, increase unit size by 5%; after a red week, cut by 10% until back above the last equity peak.
- Cap correlated exposure: no more than 1.5R combined risk across instruments that move >0.7 correlated with your primary index.
Psychological Guardrails That Actually Hold
Discipline is a system, not a feeling. Bake accountability into the workflow so emotions never get a vote.
- Pre-commit in writing: what would stop you trading today (sleep <6h, illness, travel)? If true, you’re flat by rule.
- Use a visible rule-break counter on your screen; any breach shuts down new trades for 24 hours.
- Replace “intuition trades” with “sandbox trades”: sim-only until they show ≥30 samples and positive expectancy.
- End each week by answering two prompts: “What rule saved me?” and “Which rule asked to be tightened?”
Size Risk First: ATR-Based Positioning That Survives Ugly Volatility
John Bannan starts with risk, not predictions. He sizes every trade off ATR so the distance to the stop defines the dollars at risk, not his mood. That keeps his position small when markets get jumpy and lets it breathe when ranges compress. He’ll risk the same fraction of equity per trade while letting ATR dictate contract count, which means a wild week never sneaks in oversized exposure. By anchoring size to volatility, he avoids turning a normal stop-out into a portfolio event.
Bannan’s baseline is simple: pick the technical stop first, measure it in ATR, then back into size so one loss equals a planned R. If ATR spikes, size shrinks automatically; if ATR cools, size scales up without forcing anything. He’ll often park initial stops around 1.5×ATR, then let the trail follow price rather than emotion. The effect is consistency—winners feel similar, losers feel contained, and compounding doesn’t get derailed by a single outlier. That’s how he stays in the game long enough for Edge to show up.
Trade the Mechanics, Not Predictions: Rules-Only Entries, Trails, and Exits
John Bannan builds his edge on mechanics, not market calls. He defines the setup, the trigger, and the initial stop before the price gets there, so the decision is already made when the candle prints. Once in, he follows a predetermined trail—often ATR-based—so exits are math, not fear. That separation between plan and outcome lets him miss plenty of moves while still compounding on the ones that meet his criteria.
Bannan’s language is “if–then,” never “I think.” If the price closes above his moving-average gate and clears a recent high, then the order goes live; if the trail is hit, then he’s out with zero debate. He rejects mid-trade edits unless a rule explicitly allows them, because tweaks in heat are just disguised predictions. By forcing every choice through mechanical gates, John Bannan keeps consistency high, drawdowns controlled, and the equity curve driven by repeatable behavior rather than opinions.
Diversify by Underlying, Strategy, and Duration to Smooth Equity Curves
John Bannan spreads risk across what he trades and how long he holds it. Instead of letting one index, one setup, or one holding period dictate results, he mixes instruments that don’t move in lockstep and pairs short swings with multi-day trends. That blend keeps any single idea from hijacking the month, especially when volatility clusters. He treats diversification as a volatility throttle, not a search for more trades.
Bannan also diversifies by strategy mechanics—one ruleset for breakouts, another for pullback continuations—so different market states still offer qualified entries. He staggers exits with a partial at a fixed R and a runner on an ATR trail, which naturally varies duration. When correlations spike, he cuts aggregate exposure rather than pretending the book is diversified. John Bannan’s goal isn’t maximum action; it’s a calmer equity curve that lets discipline stick.
Use Cycle Watchlists, Act Only When Price Confirms the Signal
John Bannan treats cycle dates as binoculars, not buy buttons. He maps potential “turn windows” a few weeks out, then waits to see if the price actually aligns—no alignment, no trade. On a flagged day, he looks for a close back above his moving-average gate and a break of the recent swing high before he even arms an order. If volatility is spiking, he tightens the trigger with a stop-limit above the high so he’s filled only on strength, not noise.
Bannan’s mantra is “watch with cycles, act with price.” If the signal doesn’t print, he cancels and moves on; the calendar never overrules the chart. When a valid trigger fires, risk is still sized by ATR, and exits follow the usual trail, keeping the overlay from morphing into a different strategy. By using cycles to focus attention but demanding price confirmation to commit, John Bannan gets the best of both worlds—prepared for turns without guessing at them.
Bear-Market Filters On; Capital Preservation Mode Before Playing Offense
John Bannan flips to defense the moment the higher-timeframe trend and price posture turn hostile. When the 50-day slips under the 200-day and price lives beneath his short-term gate, his default is stand-aside or half-size probes only. He won’t chase bounces without a genuine follow-through day, because bear rallies vanish fast and punishment is swift. Capital protection is the job; participation is optional.
Once back in, Bannan accepts base hits over hero trades—wider stops, closer targets, and faster trails. He caps aggregate exposure, avoids stacking correlated longs, and refuses to “average down” while volatility is elevated. Any rule break triggers a cooldown day, because discipline is harder when markets are violent. That’s how John Bannan exits rough patches with both capital and confidence intact, ready to press when the wind shifts.
John Bannan’s core lesson is simple: your biggest improvements come during drawdowns—use them to upgrade the system, not your stress levels. He repeatedly emphasizes pausing to investigate what failed, then returning with a specific rule tweak, a habit he credits to hard-earned experience through rough cycles. He favors liquid index futures and leans long-only on the S&P and Nasdaq to avoid single-stock landmines, preferring instruments where gaps are about the market, not a CEO’s backyard pool.
On timing, Bannan Bicycles’ “turn-date” overlay with price-based confirmation and plain-math tools—ATR and moving averages—so the calendar narrows focus, but price makes the decision. He’s explored repeating cycles since 2013, yet insists they’re an attention aid rather than a trade trigger; entries still require traditional signals and strict risk sizing. Finally, managing outside capital sharpened his discipline: accountability to others forces faster post-mortems, cleaner rule enforcement, and a relentless push to improve during inevitable slumps.
