coding-kitties/investing-algorithm-framework
Framework for quantitative trading. Complete framework for development, backtesting, and deploying automated trading algorithms and trading bots. observed · 2026-08-28
Health v2 · maintenance only
90/100
- Activity 98
- Release rhythm 73
- Longevity 100
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: 1.0
- age_days: 2450
- days_rel: 101
- days_push: 13
- n_releases_24m: 163
Adoption not part of the score
1714 stars · 250 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A Python framework for developing, backtesting, and deploying quantitative trading algorithms and trading bots. It supports vector and event-driven backtesting, strategy comparison dashboards, and production deployment to local or cloud environments.
Use cases
- backtest crypto trading strategies on historical data
- build and deploy an automated trading bot
- compare multiple trading strategies in a dashboard
- run Monte Carlo simulations to validate strategy robustness
- compute performance metrics like Sharpe ratio and max drawdown
- deploy a live trading algorithm to AWS Lambda or Azure Functions
- rank and filter a universe of symbols with cross-sectional pipelines
When to choose
- you want a full quant workflow (strategy, backtest, compare, deploy) in one Python framework
- you trade crypto or other markets and need both vector and event-driven backtesting
- you need built-in performance analytics and statistical robustness testing
- you want to move from research to live trading with the same codebase
When to avoid
- you need a lightweight backtesting library without deployment features
- you require broker integrations or asset classes not supported by the framework
- you prefer point-and-click trading platforms over writing Python code
- you need guaranteed low-latency high-frequency trading execution
Facets
framework · maturity active
trading benchmarking analytics workflow-automation fintech python cross-platform cloud algorithmic-trading backtesting trading-bot quantitative-trading crypto-trading strategy-development event-driven-backtesting vector-backtesting portfolio-management live-trading cryptocurrency quantitative-finance automation
2 sources
- readme: https://github.com/coding-kitties/investing-algorithm-framework · fetched 2026-08-28 · 1f71cd9cba6e
- homepage: https://coding-kitties.github.io/investing-algorithm-framework/ · fetched 2026-08-29 · 89f628f8d15f
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| coding-kitties/investing-algorithm-framework | main | 90 |
For agents
markdown · JSON · MCP: product_card(name="coding-kitties/investing-algorithm-framework")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem