nanoHedgeLABS scans a vast equity universe, ranks long/short setups and keeps market context and risk beside every result. One transparent research terminal.
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This is a research screen, not a trading screen. It refreshes every 10 minutes. Start with SIGNALS: each row is a model classification, shown with its trigger, Edge band, R/R — Reward / Risk, a measured comparison between space to the first objective and distance to invalidation — macro context and technical references. Use MACRO to understand the broader context around those rows. A row helps you inspect what the model observed; it never tells you what to do.
| TICKER | NAME | EDGE ↓ ? | R/R ? | CLASSIFICATION ? | MACRO ? | TRIGGERS ? | INVALIDATION ? | 1ST OBJECTIVE ? |
|---|---|---|---|---|---|---|---|---|
| Connecting to markets… | ||||||||
| SECTOR | ETF | CONTEXT ? | REL.STR 20d ? | % CHG 20d |
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The nanoHedgeLABS team has defined a curated equity universe. Every ten minutes, the system applies the same technical and macro analysis to every covered ticker, then reduces that work to a focused research list. It identifies and ranks market configurations for further inspection; it does not recommend, open or manage a trade.
The flow above is the compact version. These six notes explain what the model examines at each stage, how the stages connect and why none of them is a standalone instruction.
The process begins with a consistent daily record: two years of candlesticks for every covered ticker. From that record the model derives price behaviour, moving averages, range, volume structure and other measurements. Input is collection and normalization, not a verdict on the name.
The weekly view establishes the broader structure before the daily chart is assessed. BULL, BEAR and NEUTRAL describe whether the larger path is supportive, adverse or mixed, so short-term observations are read within a defined market regime rather than in isolation.
T1–T5 are nanoHedgeLABS’s in-house intelligence layer. These proprietary rule families look for specific relationships between price, structure, volatility and volume that merit a structured review. They initiate research; they do not, alone, forecast an outcome or issue an instruction.
Once the evidence is present, the model maps the technical invalidation and first objective. Their measured distance creates R/R—Reward / Risk—which compares the observable space to the first objective with the distance to invalidation. These are references for inspecting the configuration, not personal stop or target instructions.
The technical map is then read through the market environment: rates, liquidity, breadth, stress, inter-sector relationships and major indicators. Context can strengthen, constrain or leave unchanged the technical evidence; it is not a probability and does not replace the underlying structure.
Only after the preceding stages are combined does the terminal display LONG, SHORT or WATCH, together with the evidence behind that label. It is a research classification for inspection, never an order, recommendation or position-sizing instruction. No active row simply means no current classification.
These are the five public trigger families introduced in step 03: T1–T5. Each is an observable market event used by the in-house intelligence layer to begin a structured review of a name. A trigger is not a trade signal; only combined evidence can produce a LONG, SHORT or WATCH classification, and many triggers produce no active classification at all.
Everything above explains how a ticker reaches the research list. The guide below explains how that result is displayed on screen. It is a reading guide for the terminal, not another stage of the model.
Each row keeps a model classification beside the evidence that produced it. Read all five groups together: the label alone is never the complete output and never an instruction.
Before reaching the final model, candidate parameters—including the 80/100 thresholds used in the model, trigger-activation rules and their calibrations—were repeatedly tested on the historical sample. The documented configuration was then applied systematically across six years and 12,374 simulated observations, including transaction costs and slippage. Profit Factor, Sharpe Ratio and hit rate describe how that configuration behaved in the test; they are not a live promise.
Figures aligned with the average of quantitative long/short equity funds. No management fees, no lock-up, no black box.
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