Case 011Position sizing and bankrollHard
A signal wins 56% of 200 even-payoff trades. What is the Kelly stake on the point estimate, what is the 95% interval for the win rate, and what stake would you actually run?
1The situation
Jharokhi Quant has a short-horizon signal that, in a backtest, won 112 of 200 trades. Each trade risks a fixed fraction of capital and either gains or loses that same amount, so the payoff is even. The trades are close to independent.
The PM asks you to size the strategy. She knows the Kelly rule and wants to know whether 56% is a number she can bet on.
2Your task
Compute the Kelly stake at the point estimate, the 95% confidence interval for the true win rate and the stakes it implies, and recommend the stake you would run, with the reason.
Quick check
Before any maths: what does the lower end of the 95% interval for the win rate imply?
Worked solution
Try it on paper, then open one step at a time.
30-second answerThe answer to give first
Kelly at 56% is a 12% stake, but the 95% interval of 49% to 63% runs from no edge to a 26% stake, so run about half Kelly, 6%. The standard error is 3.5 points. A sceptical prior worth 200 trades at 50% shrinks the estimate to 53%, whose Kelly is 6%. Betting 12% when the truth is 53% earns nothing, while 6% at a true 56% keeps 75% of the maximum growth.
Step 1What does Kelly say if 56% is the truth?
For an even-payoff bet the Kelly stakeThe fraction of capital to bet that maximises the long-run growth rate of wealth, found by maximising the expected logarithm of wealth after each bet. is the win rate minus the loss rate: 0.56 minus 0.44, 12% of capital per trade. At that stake the expected log growth is about 72 basis points a bet, the most any fixed stake can earn if 56% is exact. That if is the whole question. A shopkeeper who stocks up for a festival based on one good season is sizing on a point estimate; the stock that arrives does not care how confident he felt.
| f^* | Kelly fraction of capital for an even-payoff bet |
| p | win rate, estimated at 0.56 |
| \text{se} | standard error of the estimated win rate over 200 trades |
Step 2How sure are you of 56%?
Not very. Two standard errors either side gives a 95% interval from 49.1% to 62.9%. Push both ends through the Kelly formula and the stake runs from nothing, because 49.1% is below the 50% at which an even bet has no edge, to 26%. The chance that a coin with no edge at all wins 112 or more of 200 is about 4.4%, so the signal is probably real, but its size is barely pinned down. A Kelly stake inherits all of that uncertainty, multiplied by two.
Step 3Why does over-betting hurt more than under-betting?
Because growth is lopsided around the peak. Betting twice the true Kelly stake earns zero growth, while betting half of it keeps three quarters of the maximum. If the true win rate is 53%, its Kelly stake is 6%, and running 12% gives expected log growth of almost exactly zero: all the variance of a strategy, none of the compounding. If instead the truth is 56% and you run 6%, you still collect 54 of the 72 basis points. The drawdowns differ too: in the continuous approximation, full Kelly has a 50% chance of halving capital at some point, and half Kelly about 12.5%.
Step 4What stake would you actually run, and why that one?
Shrink the estimate, then apply Kelly to the shrunk number. A backtest win rate is usually the best of several variants tried, so it is biased up. Treat it as if you had also seen 200 trades at 50%: the estimate becomes 53%, its Kelly stake is 6%, which is half Kelly on the raw number. Run that, track the live win rate, and let the stake drift towards the live estimate as trades accumulate. After another 400 live trades the standard error halves, and you will know whether the edge is 53% or 56%.
Say the limits. Kelly assumes independent bets with known odds; real trades cluster, payoffs are not exactly even, and a strategy can stop working altogether, which no amount of shrinkage handles. Half Kelly is a starting point that is robust to the most likely error, not an optimum.
Where candidates lose it
The common loss is computing 12% and stopping, as if the backtest win rate were a known probability. The interviewer gave you only 200 trades precisely so that the interval would reach below 50%; a candidate who never computes it has sized on noise.
The second is shrinking the stake for the wrong reason, saying half Kelly because it feels safer. The argument that lands is quantitative: over-betting a 53% edge at 12% earns zero growth, under-betting a 56% edge at 6% keeps three quarters of it.
What the interviewer asks next
- The payoff is 1.2 to 1 instead of even, still at a 56% win rate. What is the Kelly stake?
- How many trades would you need before the 95% interval excludes 50% by a clear margin?
- You run three such signals with correlation 0.3. How does that change the stake on each?
- Live, the first 100 trades win 51%. What do you do with the stake?
Company names and figures are illustrative.
