Metrics

Omega Ratio

The probability-weighted ratio of gains to losses above/below a threshold, capturing the entire return distribution.

Formula

Omega = Σ max(daily_pnl, 0) / Σ |min(daily_pnl, 0)|

More Details

What is the Omega Ratio?

The Omega Ratio, introduced by Keating and Shadwick in 2002, is a comprehensive performance metric that captures the entire distribution of returns — not just the mean and standard deviation like the Sharpe Ratio.

Think of it as a more complete version of the Profit Factor, but applied to your daily returns instead of individual trades. It separates all daily returns into gains (above a threshold) and losses (below the threshold), and computes the ratio.

Formula

Omega Ratio = Σ max(daily_pnl, 0) / Σ |min(daily_pnl, 0)|

Where:
- The numerator sums all positive daily P&L values (gains)
- The denominator sums the absolute values of all negative daily P&L values (losses)
- The threshold is typically 0 (breakeven)

This is equivalent to:

Omega = (Sum of all daily gains) / (Sum of all daily losses)

Interpretation

Omega Ratio Meaning
< 1.0 Total daily losses exceed total daily gains — losing system
= 1.0 Break-even on a daily basis
1.0 – 1.5 Marginal edge
1.5 – 2.5 Good — gains meaningfully exceed losses
2.5 – 4.0 Strong performance
> 4.0 Excellent (verify adequate sample size)

How Omega Differs from Profit Factor

They look similar but measure different things:

Profit Factor Omega Ratio
Unit Per-trade Per-day
Captures Trade-level P&L Daily aggregate P&L
Skew/kurtosis Partially Fully
Multiple trades/day Counted separately Aggregated

If you take 5 trades in a day — 3 winners totaling +$400 and 2 losers totaling -$300 — the Profit Factor uses all 5 data points. The Omega Ratio sees one data point: +$100 for that day.

Why Omega Captures What Others Miss

The Sharpe Ratio only uses mean and standard deviation (first two moments). The Omega Ratio effectively incorporates all moments — mean, variance, skewness, and kurtosis — because it uses the actual distribution of returns rather than assuming normality.

This means:
- Fat tails are properly captured
- Skewed returns are fairly represented
- Non-normal distributions (which most trading returns are) don't fool the metric

A Practical Example

Over 30 trading days:
- 20 winning days totaling +$8,000
- 10 losing days totaling -$3,500

Omega = $8,000 / $3,500 = 2.29

For every dollar lost on a down day, this trader makes $2.29 on up days. That's a solid edge.

How TradesViz Calculates It

TradesViz groups your realized P&L by calendar date, separates positive and negative days, sums each group, and divides. Zero P&L days are excluded (they don't contribute to either side).

How TradesViz Does It Better

  • Compared alongside Profit Factor to spot differences between trade-level and day-level performance
  • Filter-aware: Compute Omega for specific strategies, symbols, or time periods
  • Handles edge cases: If you have no losing days, the ratio is displayed as "∞" rather than causing an error
  • Custom dashboard widget for daily monitoring

Where to find it in TradesViz

Summary > Overall Statistics > Scores/Metrics tab shows the Omega Ratio for your account. Also available as a custom dashboard widget under Misc Stats. Use global filters to compute Omega for specific setups or date ranges.

Example

20 winning days totaling $8,000 and 10 losing days totaling $3,500 gives an Omega Ratio of 2.29.