where p = win probability, q = 1−p = loss probability, B = net odds (win B per unit staked, lose 1).
Why: Weighted average of outcomes. Win B with probability p, lose 1 with probability q.
Bet fraction f of current wealth W:
Why: You keep the unbet portion W(1−f) regardless. On a win you collect B times your stake Wf on top. On a loss your stake Wf is gone.
After h wins and (n−h) losses:
Why: The flips compound — each one rescales whatever the previous left. That means multiply, not add. Order doesn’t matter, only h and n−h.
Take the nth root of total growth to extract the per-period rate:
As n → ∞, law of large numbers: h/n → p, (n−h)/n → q.
Why nth root: Same logic as extracting r from (1+r)n = total growth. Geometric mean, not arithmetic, because the process is multiplicative.
Define g = ln(G). Since ln is monotonically increasing, maximizing g gives the same f* as maximizing G.
Apply two log rules:
Why: Differentiating a product of powers is a mess. A sum of logs is trivial. Valid because ln is monotone — same maximum, easier math.
Rule: ddx[ln(x)] = 1x. Chain rule: multiply by derivative of the inside.
Set dg/df = 0:
Cross-multiply:
Expand:
Collect f terms:
Since p+q = 1:
Read as: edge / odds
Special case B=1 (even money): f* = p−q
Your optimal bet equals your raw edge.
| What | Why it matters |
|---|---|
| Multiplicative wealth function | One bad bet can’t be offset by other bets — sizing matters |
| Geometric mean not arithmetic | Compounding processes need per-period rates, not averages |
| ln transform | Turns product into sum without moving the maximum |
| Chain rule on ln(1−f) | The −1 derivative is what creates a finite optimum |
| p+q=1 | The simplification that closes the algebra cleanly |
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