What you will learn
- Understand what the Kelly criterion optimizes
- Apply the Kelly formula to size a bet
- See why over-betting ruins even a winning edge
- Know why practitioners use fractional Kelly
The position-sizing lesson said how much you bet is a matter of survival, and promised a way to make the optimal size mathematically precise. The Kelly criterion is that answer. Developed by John Kelly at Bell Labs and used by well-known investors and gamblers, it gives a formula for sizing a series of bets to maximize the long-term growth of capital, tying together expected value, compounding, and risk of ruin.
The Kelly criterion explained, with proof (Simple Explanations)
Derives the formula and shows what it optimizes. Focus on why it maximizes long-run growth, not single-bet expected value.
What Kelly optimizes
The Kelly criterion prescribes betting an amount proportional to your edge: more when your advantage is larger, less when it is smaller, and nothing when you have no edge. Crucially, it does not maximize the expected value of any single bet. It maximizes the long-term geometric growth rate of wealth, the rate at which capital compounds over many repeated bets. A strategy that maximizes single-bet expected value can still ruin you through over-betting, whereas Kelly optimizes the growth of wealth across a long sequence, accounting for how gains and losses compound.
The formula in symbols
- f = fraction of capital to bet
- p = probability of winning
- q = probability of losing (1 − p)
- b = net odds on a win
For a simple even-money bet, where b equals 1, this simplifies to f = p − q, which is the same as 2p minus 1. So with a 60 percent chance on an even-money bet, you would stake 2 times 0.6 minus 1, which is 0.2, or 20 percent of your capital.
Key terms
- Kelly fraction
- The share of capital to bet that maximizes long-run growth: (b·p - q) / b.
- Geometric growth rate
- The rate at which wealth compounds over many bets, what Kelly maximizes.
- Fractional Kelly
- Betting a portion (such as half) of the Kelly amount for a smoother ride.
Sizing an even-money bet
You have a 60 percent chance of winning an even-money bet (b = 1). What fraction of your capital does full Kelly say to stake?
- Identify the pieces. p is 0.6, q is 0.4, and b is 1.
- Apply the simplified formula. For even money, f is p minus q, which is 0.6 minus 0.4.
- Compute. That is 0.2, or 20 percent.
Why it matters: The bet is proportional to the edge. With a 60/40 advantage, 20 percent maximizes long-run growth. A bigger edge would justify a bigger fraction, and no edge would justify zero.
Compute a Kelly fraction
You have a 55 percent chance of winning an even-money bet (b = 1). What fraction of your capital does full Kelly prescribe? (Give a decimal.)
Why over-betting destroys growth
The main insight connects straight to position sizing and risk of ruin. Even with a genuine edge, betting too much on each opportunity leads to ruin rather than riches, because losses along the way compound destructively and can wipe out your capital before the edge expresses itself. Betting too little leaves growth on the table. Kelly finds the precise fraction that balances these two failures, aggressive enough to harness the edge but conservative enough to survive the losses. It is the mathematical form of the survival-enables-compounding principle.
Bet too much and even a winning edge ruins you, bet too little and you crawl. Kelly finds the fraction that compounds fastest while surviving.
The Kelly criterion: how much to bet (Zerodha)
A practical take on applying Kelly and why full Kelly is so aggressive. Watch for the case for betting a fraction of it.
Full Kelly and fractional Kelly
Betting the full Kelly amount is aggressive and produces large, stomach-churning swings with deep drawdowns. So many practitioners use fractional Kelly, betting some portion, such as half. Fractional Kelly gives up a little of the theoretical maximum growth in exchange for substantially smoother performance and shallower drawdowns, a trade most investors gladly make, especially given the drawdown asymmetry from earlier. A smaller bet also provides a margin of safety against the estimation errors discussed next.
The critical limitation: you must know your edge
Here is the catch that makes Kelly risky to apply naively in markets. The formula needs accurate estimates of your edge and the odds, and in investing these are rarely known with any precision. Your true edge is usually unknown and easy to overestimate, and overestimating it leads directly to over-betting, which Kelly itself shows causes ruin. The math is precise, but only as reliable as its inputs, and market inputs are deeply uncertain. This is the garbage-in, garbage-out principle from Unit 5 applied to bet sizing, and it is a central reason practitioners favor conservative, fractional Kelly over trusting an overconfident estimate of their advantage.
Over-betting a real edge
An investor has a genuine edge and full Kelly says to bet 10 percent of capital per opportunity. Instead, feeling confident, they bet 50 percent each time. What is the likely result over many bets?
Betting 50 percent when Kelly says 10 percent is massive over-betting. Even with a genuine edge, losses compound destructively at that size, so the likely long-run result is ruin, not faster wealth. This is the core danger Kelly identifies.Why bet less than full Kelly?
In your own words, explain why many skilled investors deliberately bet less than the full Kelly amount.
Write an answer before comparing it with the model response.
Model answer
Full Kelly maximizes theoretical long-run growth but does so with violent swings and deep drawdowns that are hard to tolerate, and the recovery math means those drawdowns are costly. On top of that, the Kelly fraction depends on knowing my true edge and odds, which in real markets I never know precisely and tend to overestimate. Since overestimating the edge leads to over-betting, and over-betting causes ruin, betting a fraction of Kelly, like half, builds in a margin of safety. I give up a little theoretical growth in exchange for much smoother performance and protection against my own estimation errors, which is usually the better trade.
Kelly formalizes bet sizing, but its inputs, and every model in this unit, can be defeated by one thing: the investor's own psychology. The next lesson confronts the behavioral pitfalls that undo good risk management.