AlgoTraders/stock-analysis-engine
Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/ observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 2908
- days_rel: n/a
- days_push: 2188
- n_releases_24m: 0
Adoption not part of the score
1238 stars · 272 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A distributed stock analysis and backtesting framework that ingests automated pricing data from IEX Cloud, Tradier, and FinViz and runs thousands of minute-by-minute trading algorithm backtests. It publishes datasets and trading performance to S3 for building AI training datasets used to teach deep neural networks how to trade, and deploys via Kubernetes/Helm or docker-compose.
Use cases
- backtest thousands of minute-by-minute trading algorithms
- fetch stock pricing, options, and news data from IEX Cloud and Tradier
- build AI training datasets of trading performance for deep neural networks
- run distributed backtesting jobs on Kubernetes with Helm
- train DNNs to predict stock closing prices
- publish compressed trading datasets to S3 automatically
When to choose
- you need to backtest large numbers of intraday trading algorithms at scale
- you want automated market data ingestion from IEX Cloud, Tradier, or FinViz
- you want to generate training datasets for deep learning models that trade stocks
- you deploy on Kubernetes or docker-compose and want Helm-based orchestration
When to avoid
- you need a maintained, actively updated project - the latest release is from 2020 and Yahoo Finance integration is broken
- you want live trading execution rather than backtesting and dataset generation
- you need a lightweight single-machine tool without Docker or Kubernetes
- you require a permissively licensed dependency - the repo has no license, restricting reuse
Facets
framework · maturity maintenance
machine-learning deep-learning etl data-science cli trading fintech machine-learning big-data python cloud self-hosted algorithmic-trading backtesting iex-cloud tradier finviz stock-market-data s3 redis minio tensorflow keras jupyter-notebooks helm-charts trading-algorithms market-data-ingestion data-engineering cryptocurrency docker kubernetes
2 sources
- readme: https://github.com/AlgoTraders/stock-analysis-engine · fetched 2026-08-28 · 3a4694d57425
- registry_pypi: https://pypi.org/pypi/stock-analysis-engine/json · fetched 2026-08-29 · f07fe5457b2e
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| AlgoTraders/stock-analysis-engine | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="AlgoTraders/stock-analysis-engine")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem