# tradytics/eiten

Statistical and Algorithmic Investing Strategies for Everyone

Repository: https://github.com/tradytics/eiten
Canonical: https://ross.abutalabs.com/products/eiten
Homepage: https://www.tradytics.com/
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: machine-learning, algorithmic-trading, investment-portfolio, portfolio-optimization, trading-strategies, trading-algorithms, tradytics, ai, statistics, eigenvalues, free-software, opensource, hedgefund, genetic-algorithm
Last push: 2022-07-30T19:01:18+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2185, "days_push": 1495, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3290, forks 367 (observed 2026-08-28T04:07:53.880588+00:00)

## What it is
Eiten is an open-source Python toolkit for building statistical and algorithmic investment portfolios, implementing strategies like Eigen Portfolios, Minimum Variance, Maximum Sharpe Ratio, and Genetic Algorithm portfolios. It includes backtesting, forward testing, and Monte Carlo simulation to evaluate generated portfolios against a market index.

## Use cases
- build optimized stock portfolios from a custom list of tickers
- backtest and forward test portfolio strategies against QQQ
- compute minimum variance and maximum Sharpe ratio portfolios
- generate eigen portfolios using PCA on stock returns
- optimize portfolios with genetic algorithms
- simulate future portfolio prices with Monte Carlo

## When to choose
- you want free, open-source quantitative portfolio construction in Python
- you want to experiment with multiple portfolio optimization strategies on your own stock list
- you need built-in backtesting and simulation to validate strategies

## When to avoid
- you need live trading execution or broker integration - Eiten only builds and tests portfolios
- you need real-time options flow or market data - that is Tradytics' paid platform, not this repo
- you need actively maintained software - the latest release dates to 2022

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, data-science, trading, benchmarking
- domain: fintech, machine-learning, data-science
- platform: python, cli, cross-platform
- tags: portfolio-optimization, algorithmic-trading, eigen-portfolios, genetic-algorithm, backtesting, monte-carlo-simulation, quantitative-finance, sharpe-ratio

## Member repositories
- tradytics/eiten (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:53.880588+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:22:49.892509+00:00, confidence not recorded.
  - readme: https://github.com/tradytics/eiten (fetched 2026-08-28T04:07:53.880588+00:00, sha 408195a055e6)
  - homepage: https://www.tradytics.com/ (fetched 2026-08-29T09:35:55.610015+00:00, sha 098787206b61)
  - site_page: https://tradytics.com/support (fetched 2026-08-29T09:35:55.612722+00:00, sha a0deed7c6c12)
- Data as of 2026-08-30T08:39:29.467469+00:00.