22 Jan, 2026
5 mins read
The Kelly Criterion is a mathematical approach used to determine the optimal size of a trade or investment. It helps traders decide how much capital to allocate to a position based on the probability of winning and the expected payoff.
In simple terms, it answers one core question: how much should you risk on a single trade to maximise long-term capital growth while avoiding ruin. Originally developed for betting, the concept later found strong relevance in trading and investing.
Understanding what is the Kelly Criterion allows traders to move away from guesswork and adopt a structured position sizing method.
Position sizing often matters more than entry or exit timing. Even profitable strategies can fail if risk allocation is poor.
The Kelly Criterion provides a framework to balance risk and reward. It aims to maximise long-term growth rather than short-term gains. By using probabilities and expected returns, traders can avoid overexposure during uncertain market conditions.
For investors, the method encourages disciplined capital deployment and helps reduce emotional decision-making.
The kelly criterion formula is expressed as:
f = (bp − q) ÷ b
Where:
f is the fraction of capital to risk
b is the net odds received on the trade
p is the probability of winning
q is the probability of losing, which equals 1 minus p
This formula calculates the ideal percentage of capital to allocate to a trade based on expected outcomes.
While the formula appears simple, accurate estimation of probabilities is crucial for reliable results.
In trading, the Kelly Criterion uses historical data to estimate win probability and reward-to-risk ratio.
First, traders analyse past performance to calculate how often a strategy wins. Next, they determine the average profit relative to the average loss. These inputs feed into the formula to estimate optimal exposure.
Instead of risking a fixed amount on every trade, position size adjusts dynamically based on edge strength. This approach helps protect capital during drawdowns and increases allocation when conditions improve.
Consider a trading strategy with a 60 percent win rate. The average winning trade makes twice as much as the average losing trade.
Here, p equals 0.6 and q equals 0.4. The value of b is 2.
Using the formula:
f = (2 × 0.6 − 0.4) ÷ 2
f = (1.2 − 0.4) ÷ 2
f = 0.4
This result suggests risking 40 percent of capital on each trade. In practice, most traders reduce this figure to manage volatility.
This kelly criterion example highlights both the power and the potential aggressiveness of the method.
The kelly criterion for investing works best when probabilities and expected returns can be reasonably estimated.
Investors may use it to decide portfolio weights, particularly when allocating between high-conviction opportunities. It is often applied in concentrated portfolios, arbitrage strategies, or systematic models.
However, long-term investors usually prefer a modified or fractional approach due to uncertainty in future outcomes.
Fixed position sizing allocates the same percentage or amount to every trade, regardless of probability or expected return.
The kelly criterion method adjusts position size dynamically. Stronger opportunities receive higher allocation, while weaker setups receive less capital.
Although dynamic sizing improves growth potential, it also increases complexity and sensitivity to estimation errors. Fixed sizing, while simpler, may underutilise high-quality opportunities.
One major advantage is capital efficiency. The method seeks to maximise long-term growth rather than short-term gains.
It also enforces discipline by linking risk directly to statistical edge. This reduces emotional trading and impulsive overexposure.
Another benefit is adaptability. Position size changes as probabilities and returns evolve, making the approach suitable for systematic traders.
The biggest limitation lies in estimating probabilities accurately. Markets change, and past data may not reflect future behaviour.
Full Kelly allocations can lead to large drawdowns and high volatility. A few consecutive losses can significantly impact capital.
The method also assumes independence between trades, which may not hold true during correlated market events.
Full Kelly uses the exact output of the formula. While mathematically optimal, it often results in aggressive position sizing.
Fractional Kelly involves risking a portion of the calculated amount, such as half or one-third. This reduces volatility and drawdowns while retaining most of the growth benefits.
Many professional traders prefer fractional Kelly due to its smoother equity curve and lower psychological stress.
Indian traders can apply this approach in equities, derivatives, and systematic strategies. However, transaction costs, slippage, and market gaps must be considered.
Retail traders should be cautious when estimating probabilities, especially in options trading where volatility changes rapidly.
Using a conservative or fractional approach is generally more suitable for Indian market conditions.
In gambling, probabilities and payouts are usually fixed and known. This makes the Kelly Criterion easier to apply.
In trading, probabilities are estimated and constantly changing. Market behaviour, liquidity, and external events add uncertainty.
While the underlying mathematics remains the same, trading requires more conservative assumptions and risk controls.
The Kelly Criterion is a powerful framework for position sizing that focuses on long-term capital growth. By linking risk to probability and reward, it encourages disciplined and data-driven decision-making.
However, its effectiveness depends on realistic assumptions and careful execution. Most traders benefit from using a fractional version rather than full allocation.
When applied thoughtfully, the Kelly Criterion can become a valuable tool in both trading and investing.
It is used to determine the optimal position size based on probability and expected return.
The formula calculates the fraction of capital to risk using win probability and payoff ratio.
Yes, but traders should use conservative assumptions and fractional allocation.
Fractional Kelly reduces volatility and drawdowns while maintaining steady growth.
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