PyPortfolioOpt | Financial portfolio optimisation in python | Portfolio library
kandi X-RAY | PyPortfolioOpt Summary
kandi X-RAY | PyPortfolioOpt Summary
. PyPortfolioOpt is a library that implements portfolio optimization methods, including classical mean-variance optimization techniques and Black-Litterman allocation, as well as more recent developments in the field like shrinkage and Hierarchical Risk Parity, along with some novel experimental features like exponentially-weighted covariance matrices. It is extensive yet easily extensible, and can be useful for both the casual investor and the serious practitioner. Whether you are a fundamentals-oriented investor who has identified a handful of undervalued picks, or an algorithmic trader who has a basket of strategies, PyPortfolioOpt can help you combine your alpha sources in a risk-efficient way. Head over to the documentation on ReadTheDocs to get an in-depth look at the project, or check out the cookbook to see some examples showing the full process from downloading data to building a portfolio.
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PyPortfolioOpt Examples and Code Snippets
- pip:
- backtrader==1.9.76.123
- livelossplot==0.5.4
- pyportfolioopt==1.4.1
- qdldl==0.1.5.post0
- osqp==0.6.2.post0
- pymdptoolbox==4.0b3
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QUESTION
Context: I'm the developer of PyPortfolioOpt, a python portfolio optimisation library, and I'm trying to allow users to add constraints to a maximum Sharpe ratio problem.
Currently, users can pass their constraints as a lambda function, e.g to make all weights greater than 1%:
...ANSWER
Answered 2020-Apr-24 at 15:35Perhaps there is some API for decomposing an already instantiated constraint so that I can put in a variable?
Constraints are immutable by design. Immutability simplifies much of CVXPY’s logic.
Why not construct a new constraint? You can certainly inspect the left and right hand sides of the constraint. Right now, that can be done by inspecting the args
attribute (see https://github.com/cvxgrp/cvxpy/blob/master/cvxpy/constraints/nonpos.py#L97).
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