westonplatter / Black-Litterman-Entropy-Pooling

Black-Litterman Entropy Pooling

Python package implementing Attilio Meucci's Black-Litterman Entropy Pooling Adaptation.

Genesis

Corey Hoffstein wrote a blog post, Combining Tactical Views with Black-Litterman and Entropy Pooling, describing an adaptation to Black-Litterman published by Attilio Meucci. The adaptation simplifies Black-Litterman by using rank ordering of expected relative instrument returns to generate asset weights.

Getting started

TODO - update as the code changes

pip install -r requirements.txt
python example.py

$ python example.py
                       Prior  Posterior
asset_class                            
Credit - High Yield     0.08   0.079390
Equity - US Small       0.06   0.060178
Bond - INT Treasuries   0.04   0.040517
Credit - REITs          0.02   0.019859
Alternative - Gold      0.00  -0.002101

Credit

Research: Attilio Meucci, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1213325.
Initial code implementation: Corey Hoffstein, https://gist.github.com/choffstein/90a1be0da8800114d00abdd9c395ff2b.
Code refinement and packaging: Weston Platter, https://github.com/westonplatter/Black-Litterman-Entropy-Pooling/.

Here's the tweet that started the codebase.

License

Copyright (c) 2017 Corey Hoffstein, MIT License.