Your edge is a moving target. NoxarQuant is the tool that tracks it.

No. Other journals record execution and ask you to tag trades by hand. NoxarQuant auto-enriches every trade with the market conditions it was taken in, then clusters them by condition and classifies each cluster by statistical edge under sample penalty. Even before the classifier has the sample size to fire verdicts, the journal layer alone is doing more than typical journaling tools. The input resembles a journal. The output is a different class of tool.

Honest answer: at 50 trades the classifier mostly returns FORMING. There isn't enough data per setup for CORE or PROMISING verdicts to fire reliably. But the journal floor is still higher than what other trading journals give you. Every trade auto-enriches with the market conditions it was taken in, then clusters against your own history. No manual tagging, no guesswork. On top of that you get behavioural breakdowns and your first NDC flags, because loss patterns surface earlier than win patterns. If you're logging daily you'll cross the classifier threshold inside 2 to 3 months. If not, treat NoxarQuant as a journal with statistical honesty until your sample grows.

No, but be honest about what you get when. The journal layer, the auto-enrichment of market conditions, the behavioural breakdowns, and your first NDC flags work from trade one. Loss patterns concentrate on identifiable conditions earlier than win patterns do. CORE and PROMISING verdicts on what's working typically firm up around 100 to 200 trades per setup. Below that, those buckets show FORMING and the tool tells you explicitly when it doesn't have enough data to judge. That staging is the point.

It is bootstrap resampling with replacement on your chronological out-of-sample segment, run up to 2,000 times depending on tier: a standard resampling technique from the statistics literature, applied to your own trades rather than a single equity curve. Whether it survives the label "hype" depends on the reader.

Yes. Exports include full cluster keys, classifications, SWI scores, and every enrichment field. JSON or CSV. The format is designed to feed TradingView, a Python research notebook, or an execution system directly.

BTC, ETH, and SOL, with full market-conditions enrichment via Hyperliquid OHLCV. Equities and futures are next; if you need a specific symbol added, email help@noxarquant.com and we'll prioritise it for the next batch.

NQ, ES, GC, SI are on the near-term roadmap. Current enrichment coverage is BTC / ETH / SOL only; equities and futures land in subsequent releases.

Start now. Create an account, upload your CSV, and your cluster map populates. No review queue, no credit card. "Founding cohort" refers to the pricing, not a gate: the price you lock in now is the price you keep. The audit pass is 3 days of full Pro access for everyone.

The audit pass gives you Pro-tier access for 3 days: cluster classification, the 3D map, PRM Before/After, and a sampled Monte Carlo (up to 3 runs during the trial). The full 1,000-simulation Monte Carlo unlocks on a paid plan. There's no free tier; after 3 days you need a paid subscription (Basic, Pro, or Elite) to keep using the app. Your trade data stays in your account either way, ready to pick back up if you subscribe later. Paid Pro is the same feature set but ongoing: new trades enrich automatically, PRM tracks over time, and you keep JSON/CSV export + history.

Yes. Systematic traders are one of the two primary founding profiles. The cluster classification identifies regime-dependent failures that often don't show up in aggregate backtests, and the JSON export feeds directly into strategy research pipelines.