> hear yet another finbro or kwant talk about leverage
> "I can make 10x my money using leverage LMFAO"
> thats how you go broke when things go wrong
> TFW every betting systems that ever existed obeys the laws of kelly
> TFW leverage or portfolio rebalancing is basically just what you do to get the Kelly you want
> TFW most ppl play it too safe in business and play it too risky in gambling
This page demonstrates the Kelly Criterion interactively. Use the slider to scale the optimal fraction.
Read comic below for further explanation on this topic. Click into the link for full comic.
Odds: Winnings multiplier (1.0 = even odds, 2.0 = double your money)
Edge: Probability of winning
Sims: Simulated trials for return/volatility analysis
Paths: Number of independent simulation runs (10-50 range)
X: Kelly multiplier
Y1: Expected log growth rate (blue curve)
Y2: Standard deviation of log growth (red curve)
Y3: Risk-adjusted growth (Green dotted)
Green shaded refers to optimal risk-adjusted Kelly range
Yellow shaded refers to growth maximizing range
Red shaded refers to ruin range
Shows 4 Kelly multiplier strategies: 0.4, 0.7, 1.0, 1.5 Kelly.
Each line shows multiple simulation paths with average highlighted
Uses 10% of sims for trials to conserve bandwidth
Click "New Simulation" to generate fresh random paths
Histogram showing distribution of final portfolio values
Overlaid histograms for each Kelly multiplier
X-axis shows log₁₀ of final portfolio values (linear scale)
Shows probability density of different outcomes
Recommended bet size should be below 0.8 K.
At K greater than 1.5, your chances of ruin gets extremely high. You notice that ruin can happen even before K reaches 1.5 when your edge or odds goes high enough.
That is another way of saying Kelly sometimes gets too overconfident in certain games, and recommends you to bet extremely big (more than 60% of your portfolio), which may work out well in few iterations, but one big loss is enough to wipe you off.
The Kelly Criterion is a mathematical formula for determining the optimal bet size to maximize long-term growth while avoiding ruin. This interactive demonstration shows how different bet sizing strategies affect portfolio growth, volatility, and risk-adjusted returns.
The Challenge: Optimal Bet Sizing
When you have an edge (probability of winning > implied by odds), the question becomes: How much should you bet?
Bet too little: You leave money on the table, grow slower than optimal
Bet too much: High volatility, risk of ruin, lower risk-adjusted returns
Bet optimally: Maximum long-term growth with acceptable risk
The Kelly Criterion provides the mathematical answer, but in practice, you often want to bet less than full Kelly for safety.
