Kelly Criterion Calculator
Calculate kelly criterion with our free Kelly criterion Calculator. Compare rates, see projections, and make informed financial decisions.
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Adjust values & calculateStrategy Analysis
Formula
The Kelly Criterion calculates the fraction of your account to risk per trade that maximizes long-term geometric growth. b is the win/loss ratio (average win divided by average loss), p is the probability of winning, and q is the probability of losing. Half Kelly and Quarter Kelly are fractional versions recommended for real-world trading to reduce volatility.
Last reviewed: December 2025
Worked Examples
Example 1: Profitable Day Trading Strategy
Example 2: Scalping Strategy Assessment
Background & Theory
The Kelly Criterion Calculator applies the following established principles and formulas. Probability theory provides the mathematical foundation for analysing all games of chance. The fundamental measure assigns a probability between 0 and 1 to each outcome by dividing the count of favourable outcomes by the count of equally likely total outcomes. Rolling a standard six-sided die produces a 1/6 probability for each face; the probability that a fair coin lands heads exactly three times in five tosses follows the binomial distribution with parameters n=5 and p=0.5. Expected value (EV) is the probability-weighted average outcome of a random variable: EV equals the sum of each outcome multiplied by its probability. A fair coin flip paying $1 for heads and costing $1 for tails has EV of zero. Casino games are designed with negative expected value for the player; the house edge is the casino's average percentage profit per bet. European roulette with a single zero has a house edge of 2.7 percent, while American roulette's double zero raises it to 5.26 percent. Poker hand probabilities derive from combinatorics. From a 52-card deck, the number of distinct 5-card hands is C(52,5) = 2,598,960. A royal flush can occur in only 4 ways, giving it a probability of approximately 0.000154 percent. Blackjack basic strategy tables, derived from computer simulation of millions of hands, reduce the house edge from roughly 2 percent to below 0.5 percent by specifying the optimal hit, stand, double, or split decision for every player hand against every dealer up-card. Sports betting implied probability converts decimal odds to a probability estimate: implied probability equals 1 divided by decimal odds. Odds of 2.5 imply a 40 percent probability. The Kelly Criterion provides the theoretically optimal bet fraction: f equals (bp minus q) divided by b, where b is the net odds received, p is the probability of winning, and q is the probability of losing. This formula maximises the long-run geometric growth rate of a bankroll.
History
The history behind the Kelly Criterion Calculator traces back through the following developments. Physical evidence of dice play dates to around 2500 BCE at the Indus Valley city of Mohenjo-daro, where excavators found carved cubic astragali remarkably similar to modern dice. Ancient Egyptian, Greek, and Roman cultures all incorporated dice games into both leisure and religious ritual, suggesting gambling emerged independently across early civilisations as a universal human impulse. The first systematic attempt to mathematically analyse games of chance came from Gerolamo Cardano, the Italian polymath who wrote "Liber de Ludo Aleae" (Book on Games of Chance) around 1564. Cardano derived correct probabilities for dice combinations and introduced the concept of sample space, though his work remained unpublished until 1663. The field transformed into a rigorous discipline through correspondence in 1654 between Blaise Pascal and Pierre de Fermat prompted by a gambling problem posed by the Chevalier de Mere. Their exchange established the rules of probability, including the concept of expected value. Jacob Bernoulli's "Ars Conjectandi" (1713) formalised the law of large numbers, proving that sample frequencies converge to true probabilities as trials increase. The 20th century brought two pivotal developments. Stanislaw Ulam and John von Neumann devised Monte Carlo simulation methods in 1947 while working at Los Alamos, showing that complex probabilistic systems could be analysed by random sampling. Game theory and poker strategy developed in parallel, with John von Neumann's minimax theorem providing early foundations and later work by game theorists formalisingrational play under incomplete information. Online gambling launched in the mid-1990s following the passage of the Free Trade and Processing Act in Antigua in 1994, which issued the first online casino licences. The Unlawful Internet Gambling Enforcement Act of 2006 disrupted US online gambling markets. Esports betting and video game loot box mechanics brought probability and expected value calculations to younger audiences in the 2010s, prompting regulatory scrutiny of randomised virtual reward systems across multiple jurisdictions.
Frequently Asked Questions
Formula
Kelly % = (b × p − q) / b | where b = Avg Win / Avg Loss, p = Win Rate, q = 1 − p
The Kelly Criterion calculates the fraction of your account to risk per trade that maximizes long-term geometric growth. b is the win/loss ratio (average win divided by average loss), p is the probability of winning, and q is the probability of losing. Half Kelly and Quarter Kelly are fractional versions recommended for real-world trading to reduce volatility.
Worked Examples
Example 1: Profitable Day Trading Strategy
Problem: Win rate: 55%, Average win: $200, Average loss: $100. What is the optimal position size?
Solution: Win/Loss Ratio (b) = $200 / $100 = 2.0\nKelly % = (2.0 × 0.55 - 0.45) / 2.0 = (1.10 - 0.45) / 2.0 = 0.325 = 32.5%\nHalf Kelly = 16.25%\nQuarter Kelly = 8.13%
Result: Full Kelly: 32.5% | Half Kelly: 16.25% | Quarter Kelly: 8.13%
Example 2: Scalping Strategy Assessment
Problem: Win rate: 70%, Average win: $50, Average loss: $80. Should you trade this?
Solution: Win/Loss Ratio (b) = $50 / $80 = 0.625\nKelly % = (0.625 × 0.70 - 0.30) / 0.625 = (0.4375 - 0.30) / 0.625 = 0.22 = 22%\nHalf Kelly = 11%\nExpectancy = (0.70 × $50) - (0.30 × $80) = $35 - $24 = $11 per trade
Result: Full Kelly: 22% | Half Kelly: 11% | Profitable with $11 expectancy per trade
Frequently Asked Questions
What is the Kelly Criterion in trading?
The Kelly Criterion is a mathematical formula developed by John L. Kelly Jr. at Bell Labs in 1956. It calculates the optimal percentage of your bankroll to risk on each bet or trade to maximize long-term geometric growth. The formula considers your win rate and win/loss ratio to determine the ideal position size. In trading, it helps determine what percentage of your account to risk per trade. However, most traders use a fractional Kelly (half or quarter) because full Kelly can lead to large drawdowns despite being mathematically optimal for long-term growth.
Why should I use Half Kelly instead of Full Kelly?
Full Kelly maximizes long-term growth rate but comes with extremely high volatility and large drawdowns. In practice, half Kelly provides about 75% of the growth rate of full Kelly but with significantly less risk and smaller drawdowns. The estimates for win rate and average win/loss are never perfectly accurate in trading, and even small estimation errors can make full Kelly dangerously aggressive. Most professional traders and fund managers recommend half Kelly or less. Quarter Kelly is even more conservative and suitable for traders who prioritize capital preservation.
How do I calculate my win rate and average win/loss for Kelly?
To calculate your inputs: 1) Win Rate = Number of winning trades / Total trades × 100. 2) Average Win = Total profit from winners / Number of winning trades. 3) Average Loss = Total loss from losers / Number of losing trades (use absolute value). You need a statistically significant sample size — at least 30-50 trades minimum, ideally 100+. These metrics should come from actual trading results or thorough backtesting. Remember that market conditions change, so periodically recalculate these values.
What does a negative Kelly percentage mean?
A negative Kelly percentage means your trading strategy does not have a positive expected value — you are expected to lose money over time. The formula is telling you not to bet at all. This can happen when your win rate is too low relative to your win/loss ratio. For example, if you win 40% of the time but your average win equals your average loss, Kelly will be negative. In this case, you need to either improve your win rate, increase your average win, decrease your average loss, or find a different strategy before risking real money.
Can the Kelly Criterion be used for forex trading?
Yes, the Kelly Criterion can be applied to forex trading, but with important caveats. Forex markets are not simple win/lose bets — outcomes are continuous, and the distribution of returns matters. The basic Kelly formula assumes binary outcomes, so it is an approximation when applied to trading. Best practices include: using fractional Kelly (half or quarter), recalculating regularly as your statistics change, accounting for correlation between trades, and never using Kelly as your sole position sizing method. Combine it with maximum risk limits (such as never risking more than 2% per trade regardless of what Kelly suggests).
Is my data stored or sent to a server?
No. All calculations run entirely in your browser using JavaScript. No data you enter is ever transmitted to any server or stored anywhere. Your inputs remain completely private.
References
Reviewed by Daniel Agrici, Founder & Lead Developer · Editorial policy