This Kelly Criterion simulator models how a bankroll can evolve across repeated bets when stake size is determined by a Kelly-based capital allocation rule. The model is probabilistic, path-dependent, and designed to show how growth, volatility, and drawdowns interact under fixed assumptions. Rather than producing a single forecast, the simulator generates many possible bankroll paths under the same input conditions.
What the Kelly Simulator Models
This Kelly Criterion simulator models bankroll evolution as a multiplicative process. Each bet changes total capital by a fraction of the current bankroll, which means growth and loss compound over time rather than accumulating in a flat linear way.
The simulator is built around repeated trials with fixed probability and fixed odds. Because the same capital allocation logic is applied across many simulated paths, the output can show how the Kelly Criterion changes long-run growth behavior, volatility, drawdown depth, and tail outcomes under stable model conditions.
The result is not a single expected bankroll number. It is a distribution of possible outcomes shaped by edge, odds, variance, and path dependency.
How the Kelly Criterion Works
The Kelly Criterion is a capital allocation formula used to determine what fraction of bankroll should be risked when a bettor or investor believes a measurable edge exists. In simple terms, the Kelly fraction increases when the perceived edge is stronger and decreases when the edge is weaker or the payout structure is less favorable.
Inside this simulator, the Kelly Criterion is treated as a formal bankroll sizing rule. The model does not decide whether an edge is real. It only shows what can happen to capital when a fixed edge assumption is translated into repeated Kelly-based exposure.
This matters because bankroll growth is not determined by win rate alone. It depends on the relationship between probability, odds, and stake size. A positive edge can still produce severe volatility if exposure is too aggressive, while a smaller capital fraction may reduce growth but also reduce drawdown pressure.
Kelly Criterion and Growth Optimality
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