alphabuilder-optimizer 0.0.1.3

Alpha optimizer library for quantitative finance research

AlphaBuilder-Optimizer

AlphaBuilder-Optimizer is an experimental Python package for building and testing optimization tools in trading and portfolio management.
It provides a clean API interface and serves as a foundation for research, development, and integration into modular trading systems.

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Current Status

The project is in its early stages. The current version includes:

• A FastAPI backend for portfolio optimization.
• An equal-weighted strategy as the initial supported method.
• A framework for extending to more optimization approaches.

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Planned Features

• Portfolio Optimization
  • Classical methods: Markowitz, Black-Litterman, convex optimization.
• Metaheuristics
  • Genetic algorithms, simulated annealing, swarm intelligence.
• Reinforcement Learning
  • Adaptive and regime-aware optimization approaches.

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Installation

You can install the package directly from PyPI:

pip install alphabuilder-optimizer

Quickstart Example

# Import
from alphabuilder_optimizer import OptimizerClient

# Initialize client
client = OptimizerClient(api_key="YOUR_API_KEY")

# Run optimization
result = client.optimize(
    idempotency_key="ALPHABUILDER042",
    assets=["asset_A", "asset_B", "asset_C", "asset_D", "asset_E"],
    constraint="equal_weighted",
    risk_free_rate=0.05,
    expected_returns=[0.1, 0.12, 0.15, 0.23, 0.56],
    covariance=[
    [0.1, 0.02, 0.03, 0.04, 0.05],
    [0.02, 0.08, 0.01, 0.06, 0.07],
    [0.03, 0.01, 0.09, 0.02, 0.03],
    [0.04, 0.06, 0.02, 0.11, 0.08],
    [0.05, 0.07, 0.03, 0.08, 0.12]
  ])

print(result) # JSON/dict with optimized portfolio weights

# Retrieve stored items
res = client.get_items()
res

Documentation

Full Optimizing Documentation Docs

Read more about the Optimizer AlphaBuilder-Optimizer

Learn more about AlphaBuilder Project AlphaBuilder