Risk: Medium

Fractional Kelly

Stake size is derived from the estimated edge and the price, then divided down (quarter Kelly) to absorb model error.

How it works

Full Kelly maximises long-run growth but is far too violent when the model is imperfect.

We take a fraction (quarter Kelly by default), which keeps most of the growth with a fraction of the swings.

When the edge is zero or negative the formula returns zero and the strategy simply declines the bet.

Formula

f* = (p × (odds − 1) − (1 − p)) / (odds − 1); stake = kelly_fraction × f* × bankroll

  • pModel probability of the selection winning
  • oddsDecimal price taken
  • kelly_fractionSlice of full Kelly actually staked, e.g. 25%

Worked example from a €10 base stake

  1. Price 2.10, model probability 0.53 → b = 1.10, f* = (0.53 × 1.10 − 0.47) / 1.10 ≈ 0.10.
  2. Quarter Kelly: 0.25 × 0.10 ≈ 2.5% of bankroll.
  3. On a €1,000 bankroll that is a €25 stake; on a €400 bankroll it is €10.

If the bet wins: The bankroll rises, and the next Kelly stake rises with it — but only when a genuine edge is present.

If the bet loses: The bankroll falls and stakes shrink. Zero or negative edge returns a zero stake and the bet is declined.

Reset conditions: No ladder to reset. Each bet is sized independently from its own edge and price.

Historical robot performance

Settled bets

2

Won / lost

1 / 1

Strike rate

50.0%

Average odds

2.95

Total staked

€20.68

Net P/L

€13.82

ROI

66.8%

Max drawdown

€10.68

Sample size: 2 settled bets. This is far too small a sample to draw conclusions from. Figures are published for transparency, not as evidence that any strategy is profitable.

Simulated bankroll: €1013.82 from a €1000.00 start. Paper mode — no real money is staked.

Advantages

  • Stake scales with the real edge
  • Best theoretical long-run growth per unit of risk

Disadvantages and risk

  • Very sensitive to probability errors
  • Large stakes on high-edge bets need the caps

Overall risk rating: Medium.

When this strategy suits

  • Situations where the probability estimate is reasonably trustworthy
  • Maximising long-run growth per unit of risk
  • Portfolios where edge size varies a lot between bets

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