A Python implementation of the Principal Portfolios methodology by Kelly, Malamud, and Pedersen (2023), enabling optimal asset allocation by exploiting cross-predictability among asset returns.
Project description
principal_portfolios
A Python package implementing the Principal Portfolios methodology introduced by Kelly, Malamud, and Pedersen (2023), The Journal of Finance.
📘 Overview
This package provides tools for constructing and analyzing Principal Portfolios—linear trading strategies derived from the singular value decomposition (SVD) of the prediction matrix that captures both own-asset and cross-asset predictive signals.
Key components include:
- Construction of the prediction matrix from asset returns and signals
- Decomposition into:
- Principal Portfolios (PPs): timeable portfolios ordered by predictability
- Principal Exposure Portfolios (PEPs): factor-exposed strategies (beta)
- Principal Alpha Portfolios (PAPs): factor-neutral strategies (alpha)
📖 Reference
Kelly, B., Malamud, S., & Pedersen, L. H. (2023). Principal Portfolios. The Journal of Finance, 78(1), 347–392.
🔧 Installation
After uploading to PyPI, install via:
pip install principal_portfolios
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