How accurate are QuantLogix signals?

Most platforms ask you to trust the signal. QuantLogix logs every signal the moment it fires and grades it against live market prices — so the accuracy below is measured, not marketed. Here's the verified win rate and average return, broken down by signal type and sector.

46.1%
of Strong Buy signals were winners · avg +1.01%
across 10,351 resolved signals — every one logged at issuance, graded against live market prices

By signal strength

Every label is graded in its own direction: Buy-side signals win when the price rises; Sell-side signals are graded as a short from the signal price — a WIN means the price actually fell, and their average return is the short-side gain. So a strong engine wants HIGH win rates on every row. The long side has cleared that bar; the short side's weak numbers below are published as-is — that underperformance is why sell-side signals now carry an evidence gate that marks weak short cohorts advisory rather than actionable.

SignalWin rateAvg returnSample
Strong Buy 46.1% +1.01% 2,318
Buy 41.4% +0.46% 4,108
Sell 42.2% -0.30% 3,095
Strong Sell 40.0% -0.37% 830

By sector × signal

Which sectors the engine reads best, ranked by win rate (samples of at least 20).

SectorSignalWin rateAvg returnSample
MaterialsStrong Sell 61.8% +3.88% 34
EnergyStrong Sell 58.1% +3.86% 43
EnergyStrong Buy 56.9% +1.88% 153
MaterialsSell 55.6% +2.06% 99
TechnologyStrong Buy 52.6% +2.88% 743
HealthcareBuy 50.8% +2.70% 360
HealthcareStrong Buy 49.6% +1.44% 232
Consumer StaplesBuy 47.9% +1.13% 73
TechnologyBuy 47.4% +2.04% 775
OtherSell 46.6% -0.49% 1,380
FinancialsStrong Sell 46.3% +0.16% 80
IndustrialsSell 46.2% +1.41% 292
OtherStrong Buy 45.5% +0.63% 1,075
OtherBuy 45.4% +0.04% 1,934
FinancialsSell 44.8% -0.22% 560
IndustrialsStrong Sell 44.1% +0.33% 93
UtilitiesSell 43.1% +0.17% 204
FinancialsStrong Buy 42.0% +0.33% 352
FinancialsBuy 41.2% +0.42% 684
EnergyBuy 41.2% +0.24% 228
OtherStrong Sell 41.2% -0.40% 405
EnergySell 40.4% -0.71% 146
CommunicationBuy 40.0% -0.41% 95
CommunicationSell 37.5% -0.24% 80
IndustrialsStrong Buy 37.2% -0.79% 180
IndustrialsBuy 37.1% -1.12% 326
TechnologySell 36.3% -1.48% 504
HealthcareStrong Sell 36.2% -1.19% 69
Consumer StaplesSell 36.1% -0.15% 61
UtilitiesStrong Buy 33.3% -2.46% 45
UtilitiesStrong Sell 33.3% -0.66% 36
HealthcareSell 33.2% -0.96% 217
MaterialsBuy 32.4% -1.09% 139
Consumer StaplesStrong Buy 31.0% -0.33% 29
MaterialsStrong Buy 28.8% -1.17% 59
UtilitiesBuy 27.1% -1.43% 210
TechnologyStrong Sell 26.7% -3.46% 150
CommunicationStrong Buy 24.5% -4.64% 49
See the statistical validation → Today's top signal Browse all signals

Measured from QuantLogix's immutable signal track record: every signal logged at issuance with entry, target, and stop, then resolved against live prices (WIN/LOSS only; open signals excluded). Win rate = wins ÷ resolved; buckets shown only at a sample of at least 20. Grading is direction-aware: Buy-side targets sit above entry, Sell-side targets below, and a Sell-side WIN means the price fell — its % return is computed as a short from the signal price, so a negative average on a sell row means those bearish calls genuinely lost. Defaults to the S&P 500 cohort. This is verified historical performance, for informational purposes only — past performance does not guarantee future results, and nothing here is investment advice. Full verified record →

FAQ — Engine Accuracy

What does the Engine Accuracy page show?

The public, graded accuracy of the QuantLogix 5-factor signal engine: hit rate by signal type and horizon, sample sizes and confidence, built from every resolved signal in the archive rather than from selected examples.

How is accuracy measured?

Every signal is logged at issuance with its level geometry and resolved against live prices; a signal counts as correct when the market moved in the signed direction of the call before the stop or expiry. Statistics are computed over the full resolved population.

Can I verify it myself?

Yes — the resolved archive and QL Signal Truth receipts are public, and QL Rewind freezes each day's rankings into a hash-chained archive so past states can be re-read exactly.