rebalanced 0.1.0

A Python framework for market simulation and investment strategy modeling, built from composable primitives

rebalanced

WIP: A Python framework for market simulation and investment strategy modeling, built from composable primitives.

Overview

rebalanced is a financial simulation framework built from composable primitives — reusable building blocks for modeling markets, portfolios, and trading strategies.

Planned Primitives

• Finite State Machines (FSM): Event-driven state transitions ✓ (implemented)
• Event Streams: Time-series data processing
• Portfolio Models: Pluggable representations of holdings
• Simulation Engine: Orchestration and lifecycle management
• Analytics: Reporting and visualization

Use Cases

• Strategy Backtesting: Simulate trading strategies against historical data
• Portfolio Rebalancing: Model rebalancing rules as composable state machines
• Market Simulation: Build agent-based models of market behavior
• Risk Analysis: Stress-test strategies across scenarios

Installation

pip install rebalanced

Packages

This is a monorepo with the following packages:

Package	Description
rebalanced	Core namespace package
rebalanced-core	TBD: Simulation orchestration engine (planned)
rebalanced-fsm	Finite state machine primitives - event-driven state transitions
rebalanced-cli	TBD: Command-line interface for the simulation engine (planned)
rebalanced-lens	TBD: Analytics and reporting (planned)

Development

This project uses uv for dependency management:

# Install dependencies
uv sync

# Run tests
uv run pytest

# Run linters
uv run ruff check .

Status

🚧 This project is in early development. APIs are subject to change.

License

Apache 2.0 License - see LICENSE for details.