The Black-Litterman Model

A mathematical approach to portfolio allocations.

Formula

E[R] = $[{\tau\sum}^{-1} + P'{\Omega}^{-1}P]^{-1}\times[({\tau\sum}^{-1}\times\pi)+P'{\Omega}^{-1}Q]$

where: 𝛕 -> tau scalar 𝝅 -> Implied Equilibrium Excess Returns ∑-> Covariance Matrix of Excess Returns Q -> View Matrix P -> Pick Matrix for views 𝝮 -> View Confidence Matrix (P(𝛕∑)P’) E[R] -> adjusted expected return matrix

To Run

1. git clone the project
2. pip install numpy and pandas
3. run python test_model.py

TODO

Calculate optimal asset allocation weights with mean-variance optimization