System Quality Number (SQN) is a trading system evaluation metric created by Van K. Tharp and introduced in his book Trade Your Way to Financial Freedom. It measures not just whether a system is profitable, but how consistently and reliably it produces that edge — combining average R-multiple per trade with outcome variance and sample size into a single score.
- SQN rewards consistency of outcomes, not just average return — a system with erratic wins and losses scores lower even if its average R is identical to a steadier system.
- Van Tharp’s minimum practical threshold is SQN 2.0 on at least 30 live trades before increasing position size on any strategy.
- The √N factor in the formula means small sample sizes inflate SQN scores — always treat scores under 30 trades as preliminary data, not a green light.
How to Calculate System Quality Number
The formula requires R-multiples for each trade — meaning each outcome must be expressed as a multiple of your initial risk, not in raw pips or dollars.
SQN = (Mean R-Multiple / Standard Deviation of R-Multiples) × √N
- Mean R-Multiple: Average R earned across all trades in the sample
- Standard Deviation of R-Multiples: Measures how spread out your trade outcomes are
- N: Total number of trades in the sample
A trade that returns exactly what you risked is +1R. A trade that loses half your planned stop is -0.5R. A trade that hits 2x your risk is +2R. Converting all outcomes to R normalizes position sizing differences across the sample.
When comparing two systems with different trade frequencies — say a scalper with 200 monthly trades vs. a swing trader with 15 — Van Tharp’s original framework normalizes SQN to 100 trades by substituting N=100 regardless of actual sample size. Some traders prefer to use actual N for accuracy; the key is to be consistent.
Quick Reference
| Aspect | Detail |
|---|---|
| Formula | (Mean R / StdDev R) × √N |
| Below Average | 1.6–1.99 |
| Average | 2.0–2.49 |
| Good | 2.5–2.99 |
| Excellent | 3.0–5.0 |
| Superb | 5.0–6.99 |
| Holy Grail | 7.0+ |
| Minimum Sample | 30 trades for reliable interpretation |
| Warning Signs | SQN below 1.6 or calculated from fewer than 30 trades |
Practical Example
A EUR/USD swing trader reviews their last 50 trades: win rate 48%, average winner +2.1R, average loser -1.0R. Mean R across all 50 trades is +0.54R. Standard deviation of R is 1.3R.
SQN = (0.54 / 1.3) × √50
= 0.415 × 7.07
= 2.94
A score of 2.94 falls in Van Tharp’s “good” range. With 50 trades in the sample, the data is statistically meaningful — this trader has grounds to consider a moderate increase in position size.
Now consider the same system where a few large losing outliers push the standard deviation to 2.1R:
SQN = (0.54 / 2.1) × √50
= 0.257 × 7.07
= 1.82
That drops to “below average.” Same mean R, same win rate — but the inconsistency in outcomes signals that the system is not yet ready to scale. The trader should identify what caused the outlier losses and work on reducing variance before increasing risk.
The System Quality Number, or SQN, is a score developed by Van Tharp that measures how good a trading system is. It combines your average profit per trade with how consistent those profits are, scaled by how many trades you have.
Common Mistakes
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Calculating SQN on too few trades. At N=10, a single +5R outlier trade can push SQN above 3.0 on an otherwise mediocre system. Treat any SQN calculated from fewer than 30 trades as directional at best.
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Using dollar P&L instead of R-multiples. If you vary position size across trades, raw dollar returns are not comparable. A $500 win on a $250 risk is +2R; the same $500 win on a $1,000 risk is only +0.5R. SQN only works correctly when inputs are true R-multiples.
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Treating SQN as a performance measure rather than a system quality gate. SQN tells you whether a system is worth scaling — it does not predict future returns. A system can score 3.0 in backtesting and 1.4 on live data. Always calculate SQN on live or forward-tested trades before scaling.
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Ignoring expectancy alongside SQN. A system with SQN 2.8 but mean R of only +0.05 is highly consistent but barely profitable in practical terms. SQN and expectancy work together — both need to be positive and meaningful.
How PipJournal Tracks System Quality Number
PipJournal calculates SQN automatically from your logged trades, converting each outcome to an R-multiple based on the stop loss distance recorded at entry. The analytics dashboard displays SQN by strategy tag, session, and date range — so you can see exactly when a strategy crossed the 2.0 threshold and was ready to scale, and whether recent trades are moving that score up or down.
