Best caseHighest finish
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Status—
Failure / horizon—
Max drawdown—
Longest loss streak—
Trades (W / L)—
Target reached—
Monte Carlo / Kelly criterion
Kelly Criterion Monte Carlo Simulator
Estimate full Kelly from win rate and payoff, scale it to a safer fraction, then watch how trade order changes growth, drawdown and survival across hundreds of bot paths.
Fractional Kelly sizingRisk recalculated from current equity
Sizing comparison
Kelly risk used—after fraction and cap
Risk of ruin—paths below the ruin floor
Chance of target—paths reaching the growth goal
Median final balance—at the horizon
Bot paths tested—independent trade sequences
All simulated equity paths
All botsBest case · Monthly maximumMedian case · Monthly medianWorst case · Monthly minimum
Hover or tap to inspect Best, Median and Worst onlyLog scale · months
Three outcome cases
Cards use the highest, middle and lowest final balances. Chart boundaries recalculate across every bot each month.
Median caseP50
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Status—
Failure / horizon—
Max drawdown—
Longest loss streak—
Trades (W / L)—
Target reached—
Worst caseLowest finish
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Status—
Failure / horizon—
Max drawdown—
Longest loss streak—
Trades (W / L)—
Target reached—
Purpose
Scale risk to the strength of the edge.
The Kelly formula estimates the growth-maximising fraction of equity from win probability and payoff. This simulator uses fractional Kelly and a hard risk cap so you can compare long-run growth with the drawdowns produced by different trade sequences.
Full Kelly is mathematically aggressive and depends on perfectly estimated inputs. Estimation error, changing edge, costs and correlated losses can make real drawdowns much worse. Fractional Kelly does not remove risk.
01
Enter a measured edge
Use realised win rate and average reward:risk from enough trades to reduce estimation noise.
02
Reduce the Kelly fraction
Quarter or half Kelly intentionally trades some theoretical growth for lower position size and usually lower volatility.
03
Check the poor sequence
Compare the true monthly worst boundary and ruin probability. If either is unacceptable, lower the Kelly fraction or maximum risk cap.
Kelly growth planning
Can Kelly sizing build wealth—and when might a target be reached?
The Kelly Criterion estimates the fraction of capital that maximizes long-run logarithmic growth when win probability and payoff are known and stable. Real estimates are imperfect, so this tool combines fractional Kelly, a risk cap and Monte Carlo paths to show how an attractive growth rate can still produce difficult drawdowns and widely different target dates.
Turn an edge estimate into a risk budget
Kelly uses win rate and reward:risk to calculate a theoretical fraction. The “Kelly fraction used” deliberately scales that number down. Quarter or half Kelly may sacrifice some theoretical speed in exchange for smaller position sizes and more tolerance for estimation error.
Translate simulated trades into months and years
The simulator groups your trade frequency into calendar months. For each case, “Target reached” is the first month its balance crosses the selected multiple. Compare all three cases: the distance between their dates is sequence risk, not a forecasting error.
Ask whether the inputs can persist
Kelly is highly sensitive to an overstated win rate or payoff. Fees, slippage, correlated trades and a changing market regime can reduce the live edge. Re-run the model with conservative inputs and a lower Kelly fraction before treating the median timeline as usable.
How to read a wealth target
If the median path reaches 10× capital in year 6 while the worst boundary falls near the ruin floor, the simulation has not proven that you will be rich in six years. It has shown the conditions required, the sequence risk around that estimate and whether the drawdown may be too severe to follow in practice. The safest useful output is often the risk setting you can sustain—not the fastest date.
Continue learning
Kelly Criterion and Monte Carlo guides.
These articles explain the assumptions behind Kelly growth, fractional sizing and risk of ruin so the simulator can support a disciplined plan instead of an unrealistic promise.
Original research · 12 min
Fixed risk versus fractional Kelly: a 5,000-path comparison
See how quarter and half Kelly changed median growth, poor-case balances, maximum drawdown and ruin against fixed-risk rules.
Explore the study → Kelly growth · 8 minCan the Kelly Criterion make you rich?
Learn what Kelly actually maximizes, why Full Kelly can feel aggressive and how estimation error changes the result.
Read the evidence-based answer → Position sizing · 8 minKelly Criterion vs fixed fractional position sizing
Compare fractional Kelly with a fixed percentage and decide which assumptions fit your risk plan.
Read the comparison → Monte Carlo · 9 minHow to read equity paths, drawdown and risk of ruin
Separate a useful stress test from a forecast before acting on an attractive simulation result.
Read the guide → Capital survival · 8 minWhy protecting capital matters more than chasing one big return
See how position risk, drawdown recovery and time interact with the compounding process.
Read the guide →