Kelly Criterion

The Kelly Criterion was developed by John L. Kelly Jr. at Bell Labs in 1956, originally in the context of information theory and signal transmission, and was subsequently adopted by gamblers and later by portfolio managers and traders. The core insight is that betting too little reduces long-term growth unnecessarily, while betting too much — even on a positive expected value proposition — can lead to ruin through volatility.

The formula calculates the optimal bet fraction as: f* = (bp - q) / b, where f* is the fraction of capital to allocate, b is the net odds received on the bet (or the reward-to-risk ratio), p is the probability of winning, and q is the probability of losing (1 - p). In investment terms, this translates to: f* = Edge / Odds, where Edge is the expected return per rupee risked and Odds is the payoff ratio.

For Indian equity portfolio managers and systematic traders, the Kelly Criterion has gained attention as a theoretically optimal position-sizing framework. If a trader's strategy has a historical win rate of 60% and an average win-to-loss ratio of 1.5:1, the Kelly fraction calculates to approximately 26.7%, meaning 26.7% of capital should be allocated to each trade to maximise long-term compounding.

In practice, full Kelly is rarely deployed because the formula assumes precise knowledge of p and b, which in real markets are only rough estimates derived from historical data. The practical approach in Indian institutional portfolio management is to use Half-Kelly or Quarter-Kelly, which accept a somewhat lower expected growth rate in exchange for significantly reduced portfolio volatility and drawdown risk.

SEBI-registered Portfolio Management Services (PMS) and Alternative Investment Funds (AIFs) in India that employ systematic or quantitative strategies have explored Kelly-based position sizing for their multi-stock strategies. The challenge in implementation is that Kelly assumes independent bets, while equity positions in a portfolio are correlated — especially in Indian markets where macro factors, FII flows, and sector rotations create high intra-portfolio correlations.

Behavioural finance research has also noted that most investors — even professionals — are psychologically unable to follow full Kelly sizing through periods of high drawdown. The Kelly framework, therefore, is most practically useful as a conceptual anchor for understanding the relationship between edge, odds, and optimal position size, rather than as a rigid mechanical rule for every allocation decision.