Probability Estimation Methods

Probability estimation methods involve calculating the likelihood of a trade outcome based on historical performance, market signals, or fundamental analysis. In trading, these estimates are the inputs for position sizing formulas like the Kelly Criterion.

Techniques range from simple frequency counts to complex machine learning models that process large datasets. In crypto, where market structure is fragmented, these methods must account for exchange-specific liquidity and order flow.

Improving the accuracy of these probabilities is the primary way to increase a strategy's edge. It requires a disciplined approach to backtesting and validation.

Accurate estimation is the difference between a profitable strategy and a failing one.