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chirindaopensource / agentic_architecture_for_institutional_asset_management

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End-to-End Python implementation of Ang et al's (2026) Agentic 'Self-Driving Portfolio'. Implements: Black-Litterman equilibrium priors, Grinold-Kroner building blocks, Campbell-Shiller CAPE analysis, Ledoit-Wolf covariance shrinkage, Risk Parity, Hierarchical Risk Parity, and Robust Mean-Variance optimization across 18 asset classes.

python json-schema portfolio-optimization quantitative-finance multi-agent-systems black-litterman mean-variance-optimization macroeconomics autogen risk-parity regime-switching llm-as-judge llm-orchestration agentic-ai hierarchical-risk-parity fiduciary-governance strategic-asset-allocation capital-market-assumptions institutional-investment modified-borda-count
  • Updated Apr 18, 2026
  • Jupyter Notebook

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