StageAnalysis
Multi-market swing trading platform built on Weinstein Stage Analysis, VCP pattern detection, and SEPA trend filtering — covering NSE, US equities, and crypto.
The Challenge
Retail investors applying Stan Weinstein's stage analysis methodology had to run their screening manually — pulling data, calculating moving averages and trend metrics by hand, and tagging each stock's stage themselves across hundreds of symbols and multiple markets.
Automating a Manual Trading Workflow
Stage analysis — popularised by Stan Weinstein — classifies stocks into four stages based on price action and moving averages, with Stage 2 breakouts as the core edge traders look for. Doing that consistently, across markets, doesn't scale by hand.
Three Screening Methods, One Platform
Rather than relying on a single signal, StageAnalysis layers Weinstein's stage classification with VCP (volatility contraction pattern) detection and SEPA trend-template filtering — giving traders more than one lens on the same universe of stocks.
Multi-Market by Default
The platform screens NSE (India), US equities, and crypto from one dashboard, so a trader working across markets isn't switching between separate tools with separate methodologies.
Self-Hosted Infrastructure
The stack runs on a FastAPI backend with APScheduler-driven jobs, a Next.js/TypeScript frontend built on shadcn/ui, and PostgreSQL with Upstash Redis for caching — deployed via Docker Compose on a self-managed Hetzner VPS behind Caddy, rather than a managed platform-as-a-service.
Our Solution
StageAnalysis automates the pipeline: a scheduled job ingests market data across NSE, US equities, and crypto, computes the technical indicators stage analysis depends on, and classifies each symbol so investors work from a ranked, filterable dashboard instead of a spreadsheet.
Tech Stack
Results
- Covers three markets from one platform — NSE, US equities, and crypto
- Combines Weinstein Stage Analysis with VCP pattern detection and SEPA trend filtering, rather than a single signal
- Scheduled data pipeline (APScheduler) keeps classifications current without manual re-running
- Deployed on a self-managed Hetzner VPS with Docker Compose and a Caddy reverse proxy