# santoshlite/EigenLedger

An Open Source Portfolio Backtesting Engine for Everyone | 面向所有人的开源投资组合回测引擎

Repository: https://github.com/santoshlite/EigenLedger
Canonical: https://ross.abutalabs.com/products/eigenledger
Homepage: https://eigenledger.gitbook.io/documentation
Language: Python
License: Apache-2.0
License Family: permissive
Topics: quantitative-finance, quantitative-analysis, stock, stock-market, backtesting, finance, portfolio-analysis, investment-portfolio, portfolio-optimization, portfolio-management, python, investment, investment-analysis, quant, futures, fintech, stock-data
Last push: 2025-09-14T01:21:40+00:00

## Health v2 (maintenance only)
Score: 52/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 41, release rhythm 40, longevity 100
- inputs: {"age_days": 2004, "days_push": 354, "days_rel": 675, "gap_med": 0, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1081, forks 135 (observed 2026-08-28T04:03:30.644445+00:00)

## What it is
EigenLedger (formerly Empyrial) is an open-source Python library for quantitative investment portfolio backtesting, analysis, and optimization. It wraps financial analysis libraries like Quantstats and PyPortfolioOpt to provide performance and risk insights for retail investors and financial institutions.

## Use cases
- backtest an investment portfolio strategy in python
- analyze portfolio performance and risk metrics
- optimize asset allocation weights
- compare stock portfolio returns against a benchmark
- run quantitative analysis on stocks and futures
- generate portfolio risk reports in a jupyter notebook

## When to choose
- you want a high-level python wrapper over Quantstats and PyPortfolioOpt
- you need quick portfolio backtesting and risk analysis in a notebook
- you are a retail investor or analyst without heavy quant infrastructure
- you want an open-source alternative to paid portfolio analytics tools

## When to avoid
- you need event-driven backtesting with granular order execution like backtrader or zipline
- you require real-time trading or broker integration
- you need ultra-low-latency or institutional-grade tick data processing
- you want a GUI-based portfolio manager rather than a code library

## Facets
- artifact type: library
- maturity: active
- function: data-science, analytics, math, data-visualization
- domain: fintech, data-science, analytics
- platform: python, cross-platform
- tags: backtesting, portfolio-analysis, quantitative-finance, portfolio-optimization, risk-analysis, stock-market, investment

## Member repositories
- santoshlite/EigenLedger (main) score 52

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:30.644445+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 2026-08-30T06:51:23.853827+00:00, confidence not recorded.
  - readme: https://github.com/santoshlite/EigenLedger (fetched 2026-08-28T04:03:30.644445+00:00, sha 16fe2562a922)
- Data as of 2026-08-30T08:39:29.467469+00:00.