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Scott Andrews sits down for a candid trader interview about how he rebuilt after the dot-com bust and evolved into a data-driven day trader. Known for turning hard lessons into repeatable processes, Scott explains why he ditched subjective chart reading for quantified rules, built a portfolio of signals, and focused on exploiting intraday volatility without overnight risk. His story matters because it shows how a methodical edge—tested, tracked, and executed with discipline—can outlast market regimes and career pivots.
In this piece, you’ll learn Scott’s core strategy mechanics—mean-reversion around the open, synthetic “gap” logic, and pre-set targets/stops—plus how he sizes, scales, and diversifies signals for different market regimes. You’ll also see his playbook for handling drawdowns, reducing risk like a “speed bump” as pain increases, and using simple stats (think t-scores and profit factor) to know when a strategy’s edge is slipping. If you’re a newer trader, this is a fast, no-fluff tour of how to turn research into rules, rules into execution, and execution into a strategy that survives long enough to compound.
Scott Andrews Playbook & Strategy: How He Actually Trades
Big-Picture Philosophy
Here’s the gist of how Scott Andrews thinks about markets: keep it simple, quantify the edge, and let stats—not opinions—drive the decisions. He focuses on repeatable opening behaviors, avoids overnight risk, and runs everything like a rules-based small business.
- Trade a small set of well-defined, repeatable patterns you can quantify in plain numbers.
- Prioritize intraday opportunities around the open; avoid holding positions overnight.
- Build and follow a written playbook; no discretionary overrides once the bell rings.
- Track expectation (win rate × average win-loss rate × average loss) for every setup you trade.
- Pause or downshift when your numbers deviate from historical baselines.
The Opening-Gap Framework (Core Edge)
Scott’s bread and butter is exploiting the opening gap in equity index futures and ETFs—behavior that repeats often enough to model. You’ll define the gap, classify it, and trade it with pre-planned entries/exits.
- Define the “gap” as today’s open vs. the prior session’s close; measure in points and in % of ATR.
- Classify: small/medium/large gap by ATR bands (e.g., small ≤ 0.35×ATR, medium 0.35–0.75×ATR, large ≥ 0.75×ATR).
- Direction matters: gap up vs. gap down; also tag “into prior range” vs. “beyond prior range.”
- Pre-compute historical “fill rate” and average excursion for each class; only trade classes with positive expectancy.
- Avoid news-driven outliers (major CPI/FOMC/Nonfarm Payrolls) unless you’ve modeled them separately.
Pre-Market Checklist
Before the bell, Scott’s process is calm and boring by design. You’ll size up the regime, check the news calendar, and set orders so you don’t chase.
- Confirm economic calendar and earnings landmines; if high-impact at/near open, reduce size or skip.
- Mark prior day high/low, close, VWAP; compute today’s ATR(14) and overnight session range.
- Size the projected gap at 9:28–9:29 ET; classify it per your ATR bands.
- If your class is “tradable,” pre-stage orders, stops, and targets; if not, no trade.
- Set a daily max loss (e.g., 1R–1.5R) and a “first 30-minute” risk budget cap.
Entry Triggers (No Guessing)
Execution is about letting the price come to your level. Scott prefers simple triggers that fire once the open prints—objective, binary, and backtestable.
- Use stop-limit orders at predefined levels (e.g., partial gap-fill zone, or break of opening range).
- For mean reversion: if the gap opens beyond your threshold and stalls, enter toward the prior close with a stop beyond the overnight extreme.
- For continuation: if the gap is “beyond range” and holds above/below the opening range high/low for X seconds, enter with the trend.
- Only one retry per setup; if the first entry fails, either reduce the size by 50% or stand down for the day.
- Cancel unfilled orders by the end of the opening range window (e.g., by 9:50–10:00 ET).
Risk Sizing & “Speed Bumps”
The secret sauce is not the entry—it’s surviving cold streaks. Scott scales risk using simple, pre-written “speed bump” rules to cut drawdowns and extend runway.
- Risk a fixed fraction of account per trade (e.g., 0.25R–0.5R per A-quality setup; 0.1R–0.25R for B setups).
- If down −2R on the day, cut size by 50%; if down −3R, stop trading for that session.
- If weekly P&L hits −4R, trade half-size for the rest of the week or until back to breakeven.
- If the monthly drawdown reaches −8R, pause all live trading and run paper-only until two consecutive positive days.
- Never widen stops intratrade; your only “discretion” is to reduce size or stop trading.
Stops, Targets, and Timing
Scott’s exit logic is tight and pre-defined. You’ll aim for areas with statistical pull (the gap-fill or OR boundaries) while keeping stops outside noise.
- Place stops beyond the overnight extreme or the opposite side of the opening range (choose one method and stick to it).
- Initial targets: partial at 0.5× gap, main at full gap-fill or OR midpoint, depending on setup class.
- If price moves +0.7R, trail to breakeven; if it stalls near target, take the fill—don’t hope.
- Time stops: if no progress by X minutes (e.g., 20–30 minutes after entry), exit at market.
- End-of-morning rule: flatten by a hard cutoff (e.g., 11:30 ET) unless in an A+ trend continuation with a live trailing stop.
Opening Range (OR) Rules
The OR carries a ton of signal. Scott treats it as both a filter and a structure that simplifies the morning.
- Define OR = first 5–15 minutes; choose a single duration for your stats (e.g., 15m).
- Mean reversion: if the gap opens outside the prior range but re-enters and holds inside OR for Y bars, bias toward a fill.
- Continuation: if price holds above/below OR and makes a clean break retest, add or trail.
- Avoid trading mid-OR chop; entries should be at edges with clear invalidation.
- If the OR range is abnormally tiny (e.g., < 0.2×ATR), cut size due to whipsaw risk.
Playbook of Setups (A/B/C Tiers)
Scott organizes trades by quality. You’ll do the same, so risk and expectations are consistent.
- A-Setups: high historical expectancy (e.g., small gap into prior range with strong fill rate); full-size, standard targets.
- B-Setups: moderate expectancy (e.g., medium gap with mixed regime stats); half size, conservative targets.
- C-Setups: exploratory or low sample; trade on sim only until n ≥ 100 samples and profit factor > 1.2.
- Promote/demote setups monthly based on updated stats; don’t marry them.
- Maintain a one-pager per setup: definition, trigger, stop, target, stats, and “gotchas.”
Regime Filters (When to Stand Down)
Not every day is yours to trade. Scott uses simple filters to avoid paying tuition to the wrong regime.
- Volatility filters: stand down when realized intraday volatility is < 0.4× its 3-month median or > 1.6× (both ends reduce edge).
- News filters: skip or half-size on days with high-impact releases in the first 30 minutes.
- Liquidity filters: if the average book depth/volume at open is abnormally thin, cut size.
- Streak filters: after 3 consecutive losing days in the same setup, trade half-size until one green day.
- Calendar filters: treat month/quarter-end opens as separate classes; only trade if they test positive historically.
Data Tracking & Fast Feedback
Scott treats record-keeping like oxygen. You’ll log the right fields so the edge gets clearer, not fuzzier.
- Log per trade: date, instrument, gap size (% ATR), direction, setup class, entry/exit time, R multiple, adherence (Y/N).
- Track rolling stats: win rate, avg win, avg loss, PF, max adverse excursion (MAE), max favorable excursion (MFE).
- Tag errors separately (entry early/late, stop move, target skip); error R should trend toward zero.
- Weekly: prune one low-edge behavior; double down on a high-edge behavior.
- Monthly: re-run expectancy by class; update A/B/C tiers and risk limits.
Execution Discipline (What to Do in the Heat)
When things speed up, Scott slows down the decisions with pre-commitments. You’ll make your playbook harder to break.
- One screen, one checklist, one order ticket—reduce noise and scrolling.
- Use OCO (one-cancels-other) brackets so stops/targets are never forgotten.
- Read the rules aloud before the open; if you can’t state them in one breath, the setup is too complex.
- After any rule breach, reduce the next day’s size by 50% and write a corrective step you can verify.
- End each session with a 2-minute “postmortem” note focusing on process, not P&L.
Instruments & Hours
Scott keeps his universe tight so he can learn the microstructure. You’ll do the same to keep your stats clean and set up timing consistently.
- Trade one primary index product (e.g., ES, NQ, or SPY/MES/MNQ equivalent); add a second only after 3 positive months.
- Focus on the first 90–120 minutes after the cash open; that’s where the gap math lives.
- No midday revenge trades; if you missed the A-setup, you missed it—log it and move on.
- Scale contracts only when the 30-day error rate (rule breaches) is < 5%.
- Rehearse the open 5 minutes before the bell; place staged orders, confirm brackets, and breathe.
30-Day Implementation Plan
The fastest way to make this real is to time-box it. Scott would say: build the rules, collect the samples, then size up—slowly.
- Days 1–5: write your one-pagers (definitions, triggers, stops/targets, stats) and backfill at least 100 samples per setup class.
- Days 6–10: sim trade at the open using your exact live workflow; log MAE/MFE and timing.
- Days 11–20: trade live at 0.1R–0.25R risk per setup; enforce the speed bumps and daily stop.
- Days 21–30: review expectancy by class; promote/demote and adjust size only if process adherence ≥ 90%.
- At day 30: either step up one notch in size or pause and fix bottlenecks—never both.
Quantify the Edge: Turn Opening Gaps Into Repeatable Trade Rules
Scott Andrews keeps it simple: define the gap, measure it, and trade it only when the numbers say there’s an edge. Instead of guessing at the bell, he classifies each open by size (relative to ATR), direction, and whether it opens into or beyond the prior day’s range. That lets him pull rough probabilities—fill rates, average excursion, and typical time-to-target—before he risks a cent. If a specific gap class hasn’t shown positive expectancy recently, Scott doesn’t touch it, no matter how “good” it looks. He treats opinions like noise and lets the stats choose the setups.
Once the class is greenlit, rules take over: pre-stage entries at defined levels, stops beyond logical structure (overnight extremes or opening range), and targets at partial and full gap-fill zones. Scott favors one retry per idea—miss or get tagged out, then either reduce size or stand down. He also time-limits trades; if the price doesn’t move as expected within a short window, he exits and preserves mental capital. The result is a repeatable morning routine that feels boring—in a good way—because every step is scripted. Over time, this turns “gap trading” from a hunch into a small, reliable factory of R-multiples.
Size Smarter: Volatility-Based Risk Per Trade With Automatic Speed Bumps
Scott Andrews treats position size like a thermostat—set by volatility, not feelings. When daily ranges expand, he dials risk per trade down; when ranges compress, he nudges it up within a hard cap. He defines risk in R, keeps A-setups at a higher fixed fraction, and B-setups at half that. The point is simple: the market’s mood determines how much heat your account can handle today.
Scott Andrews also installs “speed bumps” to survive cold streaks. Down −2R on the day? Cut size by 50% automatically; at −3R, stop trading. If the week hits −4R, he trades half-size until back to breakeven. No widening stops, no revenge sizing—just smaller chips, same edge, longer runway.
Diversify the Day: Mix Underlyings, Setups, and Holding Durations
Scott Andrews doesn’t rely on a single trade to carry the session; he spreads bets across uncorrelated edges. He rotates between index products (e.g., ES/MES and NQ/MNQ) and only takes one trade per instrument per setup class to avoid doubling the same risk. Each setup runs with its own predefined stop, target, and size, so a loser in one sleeve doesn’t contaminate the others.
He also staggers time exposure—quick gap-fills, slower opening-range retests, and occasional trend continuations—so not every trade depends on the same ten minutes after the bell. Scott Andrews caps risk per “bucket” (underlying, setup type, and time window) and limits total concurrent exposure, ensuring a cluster of signals can’t sink the day. If correlation spikes—both instruments moving tick-for-tick—he treats them as one and halves the size or skips the duplicate. The goal is simple: more small, independent edges, fewer all-or-nothing bets.
Mechanics Over Prediction: Pre-Stage Entries, Stops, Targets, Then Execute
Scott Andrews treats execution like a checklist, not a debate. Before the bell, he pre-stages orders at clearly defined prices, attaches OCO brackets, and double-checks position size against the day’s volatility. Once the open prints, the job is to execute the plan, not to narrate the tape. If price tags his entry and structure breaks, the stop fires—no edits, no pleading with the market.
After entry, Scott Andrews manages by rules, not vibes. He moves to breakeven only after a predefined profit threshold, takes partials at mapped targets, and enforces a hard time stop if momentum stalls. If slippage appears or liquidity thins, size is cut on the next trade automatically rather than “making it back” on the current one. The whole approach says mechanics beat prediction: write the rules when you’re calm, follow them when you’re excited, and let the numbers—not impulses—decide what happens next.
Process Discipline: Daily Checklists, Opening Range Filters, Hard Time Cutoffs
Scott Andrews starts every session with a short, repeatable checklist: news scan, levels marked, gap classified, orders staged, risk confirmed. He commits to a fixed opening range definition so the morning has structure instead of guesswork. If the price is chopping mid-range, he waits; if it’s testing edges with clean validation, he acts. The checklist trims decisions to yes/no questions and keeps his head clear when volatility spikes.
Once in a trade, Scott Andrews follows hard time cutoffs to prevent slow bleeds and decision fatigue. If momentum fails to show within the first window, he exits and resets rather than negotiating with the chart. After two process breaches in a day—like moving a stop or chasing—he powers down and protects the account. Discipline isn’t an ideal here; it’s a daily operating system that makes every rule easier to keep tomorrow.
Scott Andrews’ core lesson is ruthless simplicity: spend most of your energy studying edges, not pressing buttons, and let quantified rules—not hunches—run the day. He learned the hard way that volatility cuts both ways, so he built a rules-first approach around the open, where behavior is most repeatable, and he measures everything in expectancy terms before risking a dollar. When regimes shift, he doesn’t pray; he pauses, rechecks assumptions, and only resumes when the numbers justify it.
On execution, Scott emphasizes that mean-reversion and gap behaviors can be traded if you’ve mapped the path between the open and the close—including typical adverse excursion—so your stops, partials, and patience reflect reality, not hope. He stresses that nothing works all the time; context and regime filters decide which playbook page to run today. That’s why he diversifies across setup classes and time windows, limits concurrent exposure, and enforces “lines in the sand” for drawdowns.
Risk management is where Scott gets obsessive. He scales risk with volatility, installs automatic “speed bumps” as losses accumulate, and treats daily/weekly pain thresholds as hard stops on himself, not just the trade. He tracks expected drawdowns by strategy and uses simple statistics—think t-scores and deviations—to flag when an edge may be slipping so he can cut size or stand down before damage compounds.
Above all, Scott runs trading like a small, data-driven business: pre-market checklists, pre-staged orders, OCO brackets, and post-trade notes that focus on process over P&L. Do the research, codify the rules, respect the regime, and protect the account. If you keep those promises, the edge compounds; if you don’t, the market will teach the lesson for you.
