I built a simple quant scanner for mean-reversion setups (ZcoreAI)

Name: I built a simple quant scanner for mean-reversion setups (ZcoreAI)
Availability: InStock
Author: tchantchov

by tchantchov·Feb 13, 2026·1 point·1 comment

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The Take

Computes a regression‑channel Z‑score across timeframes and presents a compact signal matrix (with an ‘expert’ view that exposes raw Z values) — a useful narrow tool if your workflow is 'find oversold across many symbols fast'. It’s a focused MVP that nails the scanning idea, but crucial details are missing: data source and backtest/validation, alert/export hooks, and a more usable workflow to act on the signals.

Post Description

Hi HN — I built a small web app that scans a list of tickers across multiple timeframes and flags potential overbought/oversold mean‑reversion setups using a regression-channel Z‑score.

Live MVP: https://zcoreai.onrender.com/

What it does:

Pick tickers + timeframes, then run a scan

Outputs a matrix of signals (simple labels now; “expert” view shows exact values of Z-Score)

Why: I wanted something fast to answer “what’s oversold / overbought right now?” without opening all charts on every timeframes on TradingView.

Notes / current state:

- Early MVP, UI is intentionally minimal

I’d love feedback on:

- Whether the output is understandable/useful

- Which features you’d want next (alerts, presets, exports, etc.)

- Any obvious UX issues or missing pieces for a tool like this

Happy to answer questions and share implementation details if people are interested.