Table of Contents
Laurens Bensdorp—quant-driven trader and author—sits down to share how he built a fully automated approach that lets him trade from anywhere while life happens. From early discretionary missteps to hiring programmers and ultimately running dozens of rule-based systems in parallel, Laurens explains why consistency beats gut feel and how automation removes the urge to meddle with trades. He also touches on lifestyle (splitting time between Europe and Colombia) and why keeping strategies simple—but combining many of them—is the secret to a smoother equity curve.
In this piece, you’ll learn Laurens Bensdorp’s core trader strategy playbook: why simple, robust entry/exit rules tend to generalize better than complex setups; how to blend non-correlated systems (long, short, mean reversion, trend) to smooth drawdowns; and how equal position sizing across strategies respects risk tolerance while avoiding “favorite child” bias. You’ll also see his take on never turning systems off based on short slumps, stress-testing for regime shifts, and the practical steps to systematize what you do now so your process runs on rails—even when markets don’t.
Laurens Bensdorp Playbook & Strategy: How He Actually Trades
Core Philosophy: Many Simple Systems, One Cohesive Process
Laurens Bensdorp runs multiple, simple, rule-based systems in parallel, so no single edge, market, or regime can make or break him. Everything is mechanical: entries, exits, position sizes, and risk controls. The goal is a smooth equity curve built from diversification by strategy, direction, timeframe, and symbols.
- Run 8–30+ independent systems (long & short, trend & mean-reversion) across a broad equity universe.
- Keep each system’s rules short, testable, and robust; avoid curve-fitting or “story” logic.
- Never override signals manually; if a rule is good enough to trade, it is good enough to follow.
- Measure success at the portfolio level, not system-by-system or trade-by-trade.
- Build redundancy: if two systems rely on the same feature (e.g., RSI), ensure others don’t.
Universe & Data: Liquid, Diverse, Daily-Driven
He targets liquid stocks and ETFs so orders fill cleanly and slippage stays predictable. Daily bars keep the process scalable and calm—scan once after the close, send orders for the next session. Breadth across sectors and market caps further reduces correlation spikes.
- Universe filter: average daily dollar volume ≥ $20M; price ≥ $5; exclude ADRs with erratic gaps.
- ETF sleeve: include major index/sector/factor ETFs for clean exposure and borrowing ease on shorts.
- Corporate actions hygiene: split/cash-adjusted data; survivorship-bias-free backtests.
- Scan once daily after the close; stage MOC/MOO/next-open orders per system rule.
- Hard cap on any single symbol’s weight across all systems (e.g., ≤ 4% of equity).
System Mix: Trend + Mean Reversion (Both Long and Short)
Laurens blends long-term trend with short-term mean-reversion, so one thrives when the other struggles. He keeps rules consistent and role-specific: trend systems hold for weeks–months; mean-reversion aims for days. Shorts are sized lighter and focus on liquid names or ETFs.
- Long Trend (example rules)
- Entry when price > 100-day SMA and 55-day breakout; no entry if 20-day ATR% > 12 (too hot).
- Exit on 20-day low or close < 100-day SMA; discretionary overrides forbidden.
- Time-stop: close the position after 120 trading days if neither exit is hit.
- Long Mean Reversion (example rules)
- Entry when RSI(2) ≤ 5, above 200-day SMA, and 3 down closes in a row; skip earnings ±2 days.
- Exit at 5-day highest close or RSI(2) ≥ 80; time-stop 7 trading days.
- No averaging down; one unit only per signal.
- Short Mean Reversion / Short Trend (example rules)
- Short MR: RSI(2) ≥ 95, below 200-day SMA, and 3 up closes; exit at 5-day lowest close or RSI(2) ≤ 20.
- Short Trend: breakdown below 100-day SMA and 55-day low; exit on 20-day high reclaim.
- Prefer index/sector ETFs for shorts; for single-names, require borrow availability and ADV ≥ $50M.
Position Sizing: Small, Consistent, and Uncorrelated
Sizing is the glue across systems. Laurens prefers equal risk per trade with volatility-aware stops so losers are tolerable and winners can compound. Portfolio heat and per-system caps prevent over-concentration.
- Risk per trade: 0.30%–0.60% of equity based on stop distance (ATR(20) multiple).
- Initial stop: 2.0–2.5 × ATR(20) from entry (system-specific, tested).
- Position cap: ≤ 1.25 × (risk% ÷ stopATR%) of equity; round down to nearest 1 share.
- Per-system open positions max (e.g., 6–12), portfolio open positions max (e.g., 35–60).
- Portfolio heat cap: sum of open risk ≤ 6%–10%; block new entries if exceeded.
Exits & Trade Management: Fast to Cut, Mechanical to Hold
Exits are pre-committed: no mid-trade tinkering. Mean-reversion targets the snapback; trend rides strength with trailing logic. Time stops unclogging the book when patterns don’t play out.
- Mean-reversion exits: fixed profit objectives (e.g., 5-day high) or RSI(2) threshold; 5–10 day time-outs.
- Trend exists: trailing on 10/20-day lows or moving-average cross; skip intraday noise.
- No partials unless explicitly tested; close full size on exit.
- If stop gaps through level, accept the slippage and log it—no “make-up” trades.
- Cancel & replace orders only at the next scheduled decision time (end-of-day).
Risk Controls: Drawdown Playbook and Daily Guardrails
The edge is the rules; the rules protect the edge. Laurens defines drawdown actions before trading, not during stress. He also sets daily guardrails to keep bad streaks from snowballing.
- Daily loss limit: if realized + open-to-close loss > 2R (or 1% equity), halt new entries next day.
- Drawdown staircase: reduce per-trade risk by 25% after 1× expected max drawdown; by 50% after 1.5×.
- Re-risk only after equity recovers ≥ 75% of the peak-to-trough drawdown.
- Slippage/TC defaults: add 1–5 bps per side for liquid stocks, 0–1 bps for index ETFs; test sensitivity.
- Overnight gap protocol: stops honored at open; no intraday overrides to “fix” gaps.
Correlation & Exposure Limits: Don’t Let One Theme Dominate
A dozen systems can still cluster if they love the same factor. Laurens caps correlation by sector, factor, and direction. The result: independent bets that behave differently when markets lurch.
- Sector exposure cap: ≤ 20% of equity per sector across all systems.
- Single-factor tilt cap (e.g., momentum, value proxy via ETF): ≤ 25% of equity.
- Long/short net exposure bands: keep -20% to +80% most of the time; allow brief excursions by rule.
- Symbol overlap rule: if two systems signal the same ticker, second order only if total risk ≤ per-symbol cap.
- Correlation audit monthly: remove or retune any system pair with 0.75+ rolling 1-year correlation.
Scheduling & Automation: One Daily Batch, Zero Discretion
The operational edge is boring on purpose. Scan, stage, and send in a single routine; then step away. Automation keeps execution consistent and frees time for monitoring health, not hunting trades.
- End-of-day scan at a fixed time; generate orders for next open or MOC, per system design.
- Broker API or automation tool places, modifies, and cancels orders; human spot-checks for borrow flags.
- Use “do not disturb” windows during the session—no chart-watching; trust the plan.
- Log every signal, order, fill, and exception; reconcile nightly.
- Weekly ops review: failed orders, borrow issues, slippage outliers, data glitches.
System Health & Research: Guardrails Against Overfitting
Laurens treats research like product development. He favors small, transparent changes with heavy out-of-sample scrutiny. New systems must add diversification, not just higher backtest returns.
- Development protocol: split data into IS/OOS; require stable OOS performance and Monte Carlo robustness.
- Parameter hygiene: use coarse grids and medians, not fragile “perfect” settings.
- Include transaction costs, borrow fees, and forced exits in tests; reject edges that vanish with friction.
- Deployment rule: add a system only if it lowers portfolio drawdown or correlation without slashing CAGR materially.
- Decommission rule: retire a system after predefined probation metrics fail (e.g., 18-month z-score < -2).
Practical Filters: Earnings, News, and Structural Landmines
Simple filters remove avoidable tail risk. Earnings gaps and structural breaks can wreck otherwise good setups; treat them as environment, not edge.
- Skip entries within ±2 trading days of scheduled earnings; hold existing positions only if rules allow.
- Exclude stocks with pending mergers, halted status, or abnormal borrow spikes for shorts.
- Avoid micro-caps and low-float squeezers; raise ADV and price thresholds during elevated VIX.
- ETF preference in stressed regimes: route short exposure into index/sector ETFs when single-name risk is jumpy.
- Holiday liquidity rule: halve per-trade risk during half-days and low-liquidity weeks.
Capital Growth & Scaling: Add Systems Before Size
Rather than simply sizing bigger, Laurens first adds non-correlated systems and symbols. Scale happens through breadth, then depth, so liquidity stays friendly and volatility stays tame.
- Milestone scaling: at every +20% equity growth, either add 2–3 symbols per system or 1 new low-corr system.
- Keep per-trade risk fixed in percent terms until liquidity forces share rounding adjustments.
- When portfolio heat hits the ceiling frequently, expand the universe before increasing risk% per trade.
- Use ETFs to bridge capacity gaps while researching single-name expansions.
- Cap single-order notional to ≤ 0.5% of ADV to minimize market impact.
Mindset: Commit to Boring, Bank on Process
The edge is repetition. Laurens Bensdorp wins by being consistent longer than others can be excited. Treat the craft like running a factory: clear rules in, controlled risk out.
- Pre-commit to rules in writing; no “one-time exceptions.”
- Evaluate monthly and quarterly, not trade-by-trade.
- Celebrate rule-following, not P&L spikes.
- If you feel the urge to “help” a trade, your rules are either unclear or you’re breaking them—fix the rules, not the trade.
- Remember: the portfolio is the product; trades are just components.
Size Risk Small, Consistent, and Let Winners Compound
Laurens Bensdorp keeps risk tiny on every single position, so no trade can hurt the portfolio more than a paper cut. He talks about defining risk in percent terms first, then translating that into shares using volatility, so size adapts automatically. The point isn’t to be right more often; it’s to survive long enough for the math of compounding to do the heavy lifting. Small, repeatable bets keep you calm and in the seat when the outliers finally show up.
He emphasizes picking a fixed risk per trade and sticking to it through hot and cold streaks alike. When a position proves itself, he lets the system ride instead of grabbing quick profits; the winners carry the month, the small losers are just the toll. Laurens Bensdorp also stresses that consistent sizing across systems prevents “favorite child” bias and keeps expectations realistic. Over time, disciplined small risk plus a few extended runs is what builds the equity curve.
Build Multiple Simple Systems for Diversification by Strategy and Duration
Laurens Bensdorp runs a stable of simple, independent systems, so no single idea can sink the ship. Each system has a narrow job—trend, mean reversion, long, short—and a clear holding period so edges don’t overlap. By mixing roles and timeframes, you get different return drivers kicking in at different times, smoothing the equity curve without trying to predict the next regime.
He keeps the rules short and testable to avoid curve-fitting, then spreads them across a broad, liquid universe. When one system cools off, another often heats up, so the portfolio keeps moving even if an individual strategy stalls. Laurens Bensdorp also caps exposure per sector, symbol, and theme, preventing the whole book from secretly becoming one bet. The result is boring, reliable progress that compounds because it doesn’t depend on any single “hero” trade.
Allocate by Volatility: ATR-Based Stops, Equalized Risk per Trade
Laurens Bensdorp sizes every position by volatility so each trade carries the same dollar risk, not the same share count. ATR sets the stop distance; risk% divided by ATR distance determines shares, making hot names smaller and quiet names larger. This keeps losses uniform even when markets speed up or slow down. It also stops you from overweighting the loudest, fastest mover just because it looks exciting.
He then standardizes this across all systems so the portfolio doesn’t tilt toward any one style by accident. Stops and targets are pre-defined, so position size is math, not mood. As volatility expands, position size shrinks automatically, keeping portfolio heat in check. Over time, this equalized-risk approach lets edges show up cleanly while Laurens Bensdorp avoids the emotional whiplash of inconsistent sizing.
Obey Mechanics, Not Predictions: Rules-First Entries, Exits, and Reviews
Laurens Bensdorp avoids guessing where price “should” go and instead follows prewritten rules that trigger entries and exits automatically. He treats signals like factory steps—if conditions A and B fire, place the order; if exit condition C hits, close the trade without debate. This removes the temptation to improvise when a chart looks tempting or scary. The structure keeps reaction time fast and consistent, which is where most discretionary traders fall apart.
He then grades performance at the rule level, not the narrative level, so the feedback loop stays clean. If a system underperforms, Laurens Bensdorp checks slippage, data, and parameter robustness rather than rewriting the story after the fact. Reviews happen on a fixed schedule, never in the heat of a drawdown, and any changes must improve portfolio-level metrics—not just the backtest of one tactic. By putting mechanics ahead of predictions, he ensures the process is repeatable even when markets feel anything but.
Cap Correlation and Exposure: Prevent One Theme Dominating Portfolio
Laurens Bensdorp treats correlation like hidden leverage—if too many trades rhyme, your real risk is bigger than it looks. He spreads bets across sectors, factors, and systems, then caps how much any one theme can occupy. That means limits per sector, per ticker, and even per style (e.g., momentum vs. mean reversion) so winners don’t all win together and, more importantly, losers don’t all lose together. He also watches rolling correlations between systems and trims or retires pairs that start moving in lockstep.
To keep control in fast markets, Laurens Bensdorp adds portfolio heat guards: if total open risk breaches a threshold, new signals wait. Short exposure leans on liquid ETFs when single-name risk spikes, and symbol overlap is throttled so multiple systems can’t pile into the same stock unchecked. Net exposure bands keep the book from drifting into accidental “all-long” or “all-short” mode. The result is a portfolio that stays balanced through chop and trend alike, because no single idea is allowed to run the entire show.
Laurens Bensdorp’s core lesson is that a durable edge comes from rules, not hunches. He moved from early discretionary swings and painful drawdowns to a fully systematic process where ideas are tested, coded, and executed mechanically—orders generated once per day and then left to play out without interference. The result is consistency: repeatable entries and exits, pre-defined risk, and a calm routine that trades from anywhere.
He favors many simple systems over one complex formula. Simple, robust rules avoid curve-fit traps, and combining uncorrelated strategies—trend and mean reversion, long and short—lets one sleeve carry the portfolio when another is in a slump. This “multiply simplicity” mindset targets higher risk-adjusted returns with lower drawdowns by design, not by prediction.
Risk is sized first, then translated into position via volatility, so no single trade can matter too much. He builds and vets each idea inside a rigorous backtesting workflow—defining objectives, choosing indicators for entry and exit, wiring position sizing, and only green-lighting systems that show a genuine edge. And when external realities change—taxes, commissions, borrowing costs—he isn’t sentimental: switch off or adapt the affected strategies immediately and keep the portfolio healthy.
