https://github.com/cvxgrp/markowitz-reference

This repository contains a reference implementation of the Markowitz portfolio optimization problem discussed in the paper Markowitz Portfolio Construction at Seventy.

https://github.com/cvxgrp/markowitz-reference

Science Score: 57.0%

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Last synced: 6 months ago · JSON representation

Repository

This repository contains a reference implementation of the Markowitz portfolio optimization problem discussed in the paper Markowitz Portfolio Construction at Seventy.

Basic Info
  • Host: GitHub
  • Owner: cvxgrp
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 14.7 MB
Statistics
  • Stars: 33
  • Watchers: 4
  • Forks: 9
  • Open Issues: 4
  • Releases: 1
Created over 2 years ago · Last pushed 7 months ago
Metadata Files
Readme License

README.md

Markowitz Reference Implementation

This repository accompanies the paper Markowitz Portfolio Construction at Seventy. It contains a reference implementation of the Markowitz portfolio optimization problem and the data used in the paper. Please note that the tickers of the stocks have been obfuscated to comply with the data provider's terms of use.

Experiments

Please run all experiments using

bash make experiments

This first installs uv on the fly and then creates and replicates the environment defined in the script section of the 'experiments.py' file as described in the documentation of uv run

If you have uv installed you can bypass make and run directly

bash uv run experiments.py

The script section is as of today

```python

/// script

requires-python = ">=3.12"

dependencies = [

"mosek==11.0.27",

"loguru==0.7.3",

"numpy==2.3.2",

"pandas[output-formatting]==2.3.1",

"matplotlib==3.10.5",

"cvxpy-base==1.7.1",

"clarabel==0.11.1"

]

///

```

A large fraction of our experiments have been performed using MOSEK as the underlying solver. We assume a valid license for MOSEK is installed. If not, you may want to apply for a Trial License

Citation

If you want to reference our work in your research, please consider using the following BibTeX for the citation:

BibTeX @article{boyd2024markowitz, title={Markowitz Portfolio Construction at Seventy}, author={S. Boyd and K. Johansson and R. Kahn and P. Schiele and T. Schmelzer}, journal={Journal of Portfolio Management}, volume={50}, number={8}, pages={117--160}, year={2024} } or for the arXiv version: BibTeX @misc{boyd2024markowitz, title={Markowitz Portfolio Construction at Seventy}, author={Stephen Boyd and Kasper Johansson and Ronald Kahn and Philipp Schiele and Thomas Schmelzer}, year={2024}, doi = {10.48550/arXiv.2401.05080}, url = {https://arxiv.org/abs/2401.05080} }

Owner

  • Name: Stanford University Convex Optimization Group
  • Login: cvxgrp
  • Kind: organization
  • Location: Stanford, CA

GitHub Events

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Last Year
  • Issues event: 3
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Issues and Pull Requests

Last synced: 6 months ago

All Time
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  • Average time to close issues: 7 days
  • Average time to close pull requests: 4 days
  • Total issue authors: 2
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  • Average comments per issue: 0.26
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Past Year
  • Issues: 1
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  • Average time to close issues: N/A
  • Average time to close pull requests: about 8 hours
  • Issue authors: 1
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  • Average comments per issue: 0.0
  • Average comments per pull request: 0.02
  • Merged pull requests: 79
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  • Bot pull requests: 91
Top Authors
Issue Authors
  • tschm (21)
  • kasperjo (3)
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Pull Request Authors
  • dependabot[bot] (224)
  • tschm (55)
  • phschiele (16)
  • kasperjo (3)
Top Labels
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Dependencies

.github/workflows/basic.yml actions
  • actions/checkout v3 composite
  • cvxgrp/.github/actions/test main composite
  • pre-commit/action v3.0.0 composite
.github/workflows/book.yml actions
  • cvxgrp/.github/actions/book main composite
  • cvxgrp/.github/actions/jupyter main composite
poetry.lock pypi
  • colorama 0.4.6
  • cvxpy 1.4.0
  • ecos 2.0.12
  • exceptiongroup 1.1.3
  • iniconfig 2.0.0
  • numpy 1.25.2
  • osqp 0.6.3
  • packaging 23.1
  • pandas 2.1.0
  • pluggy 1.3.0
  • pybind11 2.11.1
  • pytest 7.4.2
  • python-dateutil 2.8.2
  • pytz 2023.3.post1
  • qdldl 0.1.7.post0
  • scipy 1.11.2
  • scs 3.2.3
  • six 1.16.0
  • tomli 2.0.1
  • tzdata 2023.3
pyproject.toml pypi