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Kelly Criterion

Glossary Term
A mathematical formula for optimal position sizing. It calculates the fraction of capital to allocate to a trade based on the probability of winning and the payoff ratio. Closelook uses a fractional Kelly approach (typically half-Kelly) to determine position sizes across all five model portfolios.

Definition & Context

The Kelly Criterion is a mathematical formula that determines the optimal bet size to maximize long-term geometric growth of capital. The formula is: f* = (bp − q) / b, where f* is the fraction of capital to bet, b is the net odds received, p is the probability of winning, and q is the probability of losing (1 − p). For even-money bets, this simplifies to f* = 2p − 1.

Full Kelly sizing is mathematically optimal but practically aggressive — it produces large drawdowns that most investors cannot tolerate psychologically. Practitioners typically use fractional Kelly: quarter-Kelly (25% of the calculated size) or half-Kelly (50%) to reduce volatility while retaining most of the growth advantage. The Kelly Criterion requires accurate probability estimates to work — overestimating edge leads to overbetting and ruin. In Closelook's prediction market framework, Kelly sizing is applied after probability calibration, using Pinnacle closing lines as the reference for true probability estimation.

Why It Matters for Investors

Position sizing determines more of your long-term returns than stock picking. The Kelly Criterion provides the mathematically optimal bet size: f* = (bp - q) / b, where b is the odds, p is the probability of winning, and q is the probability of losing. Full Kelly maximizes long-term growth rate but produces extreme volatility — most practitioners use fractional Kelly (quarter or half) for practical portfolio management.

Closelook applies Kelly-based sizing across all reference portfolios. In the Derivatives portfolio, each options position is sized based on estimated edge and probability of profit. In Structural Narrative positions, fractional Kelly determines allocation weight based on conviction level and downside risk. The framework prevents both over-concentration (risking ruin) and over-diversification (diluting edge).

Related Concepts

Kelly Criterion connects to Alpha (you need edge before you size), Sharpe Ratio (risk-adjusted returns improve with proper sizing), and Maximum Drawdown (fractional Kelly limits catastrophic losses).

How Closelook Uses This

How Closelook sizes positions →
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