Monte Carlo Simulator – 10,000 Possible Futures of Your Account

~6 min – the probabilistic crystal ball that takes your actual trade stats and runs thousands of parallel universes to show exactly how your account might grow… or blow up… so you can size positions like a quant instead of a gambler

You’ve already dissected every angle of your past trades: drawdowns carved deep, fees quietly eaten, streaks exposed tilt, holding times revealed greed/fear, and exits ranked by quality.

Now open Monte Carlo Simulator (sidebar → FlaskConical / chart icon, route `/monte-carlo-simulator`).

This is the page where history becomes a probability cloud. It grabs your real completed-trade parameters (win rate, avg R win/loss, PnL mean/stddev, trades/day, Sharpe, max DD, etc.) from the active portfolio, then simulates thousands of possible futures — varying sequences of wins/losses, compounding (or static) risk, time horizons — to show:

• Portfolio growth paths with confidence bands
• Drawdown nightmares and recovery odds
• Kelly-optimal sizing (theoretical vs simulation-tested)
• Custom scenarios (“what if my win rate improves 5%?”)
• Every past run saved for comparison

It answers the question that keeps funded traders up at night: “If I keep trading exactly like this… what are the real odds I survive the next year — and how big can I safely go?”

Where to Find It

• Sidebar → Monte Carlo Simulator (FlaskConical / chart icon)
• Direct route: `/monte-carlo-simulator`
• Also reachable from CharterElite or Council (e.g. Drawdown → “Simulate future risk” links)

Landing Page – Validation & Launch Pad

Page header: “Monte Carlo Simulator – Run simulations to analyze portfolio performance, risk, and optimal position sizing.”

Portfolio dropdown (when multiple exist): select active portfolio — simulations run on its completed trades only.

Validation alerts (when not on History tab):

• Cannot Run (destructive red): list of fatal errors
• “Need at least 10 completed trades”
• “Win rate must be greater than 0%”
• “No trading data available”

• Recommendations (warning yellow):
• “Recommend 30+ trades for reliable stats”
• “Standard deviation is 0 — results may be unstable”
• “Average P&L seems unusually high — verify data”

Two Educational Accordions (expand first):

1. Why Monte Carlo Simulation is Your Ultimate Risk Management Tool

Benefits: see thousands of futures, confidence intervals, Kelly sizing, scenario testing; pro tip workflow: Growth → Drawdown → Kelly → Scenario.

1. Complete Guide to Every Monte Carlo Analysis Tool

Brief on each tab + tips (1,000+ sims, re-run monthly, 30+ trades ideal).

Tabs – The Six Simulation Engines

1. Summary Dashboard

No sim run needed — shows derived parameters (win rate, avg P/L, trade count, Sharpe, avg R win/loss, max DD, etc.) Six stat cards + Performance Summary card Four shortcut cards to other tabs (“Run Growth Simulation”, etc.)

1. Portfolio Growth

User params: initial_balance (from portfolio starting_balance or default 10k), num_simulations (≥1k), time_horizon_days, risk_method (starting/current), risk_percent, win_rate, avg_r_win/loss, trades_per_day (auto or custom), break_even_rate Runs portfolio_growth job → median path + 5th/95th bands, final value distribution, sample paths Charts: growth paths, final value density

1. Drawdown Analysis

Params: num_simulations, time_horizon_days, confidence_levels (e.g. 95%, 99%) Runs drawdown_analysis → max DD distribution, recovery periods, risk-of-ruin style stats Charts: max DD histogram, recovery time, confidence stats

1. Kelly Optimization

Params: num_simulations, time_horizon_days, confidence_levels Runs kelly_optimization → tests multiple fractions (25%, 50%, 75%, 100%, 125%, 150% of Kelly) → picks best Sharpe Charts: position size vs final value / Sharpe; theoretical vs simulation-tested optimal

1. Scenario Analysis

Predefined scenarios (improved win rate, reduced volatility, better R:R, bear/bull market) or custom params Runs scenario_analysis → baseline vs scenario paths/comparison charts

1. Simulation History

List of past runs (from `monte-carlo-simulator/user-simulations?limit=100`) Filter/sort by name/date/type/final value/win rate; view details, delete Card view or table; tags in localStorage

Quick Workflow – Monte Carlo Murder Ritual

1. Open Monte Carlo Simulator → expand accordions for context
2. Select active portfolio (dropdown) — parameters auto-load from its completed trades
3. Validation red? → Fix (close more trades, win rate >0, etc.)
4. Summary Dashboard → quick parameter sanity check
5. Portfolio Growth → run default sim → see median path + worst-case bands
6. Drawdown Analysis → run → check max DD percentiles & recovery odds
7. Kelly Optimization → run → compare theoretical Kelly vs sim-tested optimal
8. Scenario Analysis → test “improved win rate +5%” or custom → compare vs baseline
9. Simulation History → review past runs → tag good ones
10. Action: worst-case DD >20–25%? → lower risk % or filter weak setups

Kelly suggests aggressive fraction? → use 50% fractional Kelly for sanity

Quick Reality Checks

• Validation blocks run? → Need ≥10 completed trades, win rate >0, non-zero data
• Results unstable (wide bands)? → Small trade count or high stddev — close more
• Kelly optimal >100%? → Overfit or small sample — cap at 50–75% fractional
• No History? → Run sims first — they auto-save
• All scenarios worse than baseline? → Edge is fragile — audit setups hard
• Wide confidence bands? → Increase num_simulations (10k+) or trades

Next: Episode 42 – Full Flywheel Mastery: Integrating Weekly Alpha → Calendar Analytics → CharterElite (Monte Carlo Simulator, Compare Charts, Missed Trades, Correlation & Portfolio, Drawdown, Equity Curve, Fee Breakdown, Consecutive Winners/Losers, Holding Time, Trade Management, Playbook Analysis, Exit Analysis, R Distribution, Temporal, Performance Ratios, PEE) → Council (Kill List, Reality Check, Setup DNA) → Evolution into the self-reinforcing compounding loop that turns monthly audits into weekly micro-kills and quarterly A-grade upgrades—without ever increasing risk % or chasing new shiny setups.

Or open Monte Carlo Simulator right now. Select your active portfolio.

Validation green? Hit Portfolio Growth → run default.

Look at the worst-case band (5th percentile).

Account still positive at horizon end? Survivable.

Worst-case underwater deep? That’s your real risk.

Now run Kelly Optimization.

Theoretical Kelly aggressive? Simulation-tested lower?

Use the conservative one.

Your future isn’t one path. It’s thousands.

Simulate them. Size accordingly.

One run at a time.

Your account’s survival odds are counting on it. 😈