Performance & Returns

The percentage of closed trades that were profitable. A psychologically compelling metric, but one that is easily misinterpreted in isolation.

How to use it: Win rate must be read alongside average win and average loss size. A 90% win rate paired with a 10:1 loss-to-win ratio is still a money-losing strategy. Conversely, a 40% win rate with a 3:1 win-to-loss ratio is highly profitable. For credit spread sellers, win rates of 70–85% are common and healthy — but only if the average loss is appropriately bounded. Always interpret win rate through the lens of Expectancy and Profit Factor.

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The ratio of gross winning P&L to gross losing P&L:

PF = (∑ Wins) / (∑ |Losses|)

A value of 1.0 is break-even; below 1.0 means the strategy is net-negative before costs.

How to use it: Values above 1.5 indicate a healthy edge; the range 1.5–2.5 is considered solid for most active strategies. Be cautious — Profit Factor is sensitive to outlier trades. A single unusually large winner or loser can distort the number significantly. Always confirm it across a meaningful sample of trades and check whether it holds up when you exclude the top and bottom 5% of trade outcomes.

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The average expected P&L per trade, representing the mathematical edge of your strategy:

E = (W% × W̄) - (L% × L̄)

where W% is win rate, W̄ is average win size, L% is loss rate, and L̄ is average loss magnitude.

How to use it: Positive expectancy is the mathematical requirement for a sustainable trading edge. It is arguably the most important single metric for evaluating a strategy. However, it must be interpreted alongside trade frequency and variance — a tiny positive expectancy with high variance and low trade frequency may not justify the capital at risk. Multiply expectancy by your average number of trades per period to estimate your expected periodic P&L, then compare that to the capital deployed.

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The realized risk-to-reward ratio — the average profit on winning trades divided by the average loss on losing trades:

Ratio = (W̄) / (L̄)

How to use it: For high-win-rate strategies like credit spreads, a ratio below 1.0 is common and mathematically acceptable — your win rate compensates. The key question is whether the combination of this ratio and your win rate produces a positive Expectancy. Use this metric to understand the minimum win rate your strategy requires to remain profitable: W%ₘᵢₙ = (L̄) / (W̄ + L̄). If your actual win rate is comfortably above that floor, your edge has cushion.

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Aggregates performance metrics across a defined series of trades treated as a single strategic campaign — for example, all credit spreads on a given underlying over a rolling quarter, or all trades within a named strategy such as "weekly SPY iron condors."

How to use it: Individual trade results are noisy. Campaign Analytics surfaces whether a repeating tactical approach is performing as a cohesive unit over time. This is the right level of analysis for evaluating strategy-level edge: rather than asking "was this trade good?", you ask "is this approach good?" Use campaigns to track whether a strategy's expectancy is improving or degrading over time, and to compare the performance of different strategic approaches head-to-head on a level playing field.