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https://github.com/gabrielabra/modfin

The ModFin project aims to provide users with the necessary tools for modeling and analyzing individual assets and portfolios.

https://github.com/gabrielabra/modfin

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    1 of 3 committers (33.3%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (16.7%) to scientific vocabulary

Keywords

finance portfolio python quantitative quantitive-finance time-series
Last synced: 5 months ago · JSON representation

Repository

The ModFin project aims to provide users with the necessary tools for modeling and analyzing individual assets and portfolios.

Basic Info
  • Host: GitHub
  • Owner: GabrielAbra
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 71.3 KB
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
finance portfolio python quantitative quantitive-finance time-series
Created almost 4 years ago · Last pushed over 3 years ago
Metadata Files
Readme License

README.md

ModFin

python version   pypi version   MIT license  

The ModFin project aims to provide users with the necessary tools for modeling and analyzing individual assets and portfolios. This package contains various modules that provide a variety of useful functions and algorithms. Here is a table of the implemented modules:

Note: Modules to be fully implemented on live libraries.

  • Analysis of Time Series
  • Bet Sizing
  • Data Structures
  • Online Portfolio
  • Option Pricing

  <!---- install ----->

Installation

Requirements

ModFin requires Python 3.8 or later and C++ build tools.

If needed, you can install the C++ build tools on Visual Studio.

Methods

The project is available on PyPI, and can be installed with pip package manager with the following command:

$ pip install modfin

Alternatively, install the package from the source using the following command:

git clone https://github.com/GabrielAbra/modfin python setup.py install

  <!---- modules ----->

Asset Screening

The AssetScreening module offers functions for screening assets based on a predetermined set of metrics. One fundamental approach is to screen assets based on smart betas (Style factors), when a given a combination of traits, are likely to be of interest to a specific investor. The ready to use functions groups are:

Metrics

This submodule provides bundles of functions that can be used to screen assets. Some of the metrics are:

  • #### Risk Metrics
    • Beta, Downside Beta, Beta Quotient
    • RSquaredScore
    • LPM
    • ...
  • #### Return Metrics
    • Annualized Return
    • Exponencial Returns
    • Log Returns
    • ...
  • #### Ratio Metrics
    • Omega Ratio
    • Sortino Ratio
    • Tail Ratio
    • ...

Screening

This submodule provides functions that can be used to screen assets. Some of the screening functions are:

  • #### Z-Score Screening
  • #### Sequential Screening
  • #### Quantile Screening  

Risk Matrix

The RiskMatrix module provides multiple functions for analyzing time series data and generating risk matrices. There are three different types of algorithms that can be distinguished as:

  • ### Sample
    • Covariance
    • Semicovariance
  • ### Estimator
    • Empirical Covariance
    • Minimum Covariance Determinant
  • ### Shrinkage
    • Shrinkage (Basic Shrinkage)
    • LedoitWolf (Ledoit-Wolf Shrinkage Method)
    • Oracle (Oracle Approximating Shrinkage)

 

Portfolio Optimization

The PortfolioOpt module provides algorithms for optimization of an a asset portfolios. The algorithms live implemented algorithms are:

  • ### Risk Parity The RiskParity algorithm is a simple algorithm that optimizes a portfolio based on the risk parity weighting.

  • Hierarchical Risk Parity

    The HierarchicalRiskParity (HRP) algorithm, implements the allocation based on the book:

    De Prado, Marcos Lopez. Advances in financial machine learning. John Wiley & Sons, 2018.

    The algorithm is a risk based optimisation, which has been shown to generate diversified portfolios with robust out-of-sample properties.

  • Inverse Variance

    The InverseVariance algorithm is a simple algorithm that optimizes a portfolio based on the provided risk matrix (usually the covariance matrix).

  • Efficient Frontier

    The EfficientFrontier algorithm provide a portfolio allocation based on the modern portfolio theory (MPT). The algoritms was first proposed by Harry Markowitz in the paper:

    Markowitz, H.M.. Portfolio Selection. The Journal of Finance, 1952.

  <!---- license ----->

License

ModFin is released under the MIT license, so the code is open source and can be used in any project, provided that the original author is credited.

Owner

  • Name: Gabriel A.
  • Login: GabrielAbra
  • Kind: user

Economics Student

GitHub Events

Total
  • Watch event: 1
Last Year
  • Watch event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 49
  • Total Committers: 3
  • Avg Commits per committer: 16.333
  • Development Distribution Score (DDS): 0.388
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
GabrielAbra g****r@a****r 30
Gabriel A 9****a 10
GabrielAbrahao m****s@g****m 9
Committer Domains (Top 20 + Academic)
al.insper.edu.br: 1

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 6 minutes
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 1.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • GabrielAbra (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 40 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 7
  • Total maintainers: 1
pypi.org: modfin

Modules for Quantitative Financial Analysis

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 40 Last month
Rankings
Dependent packages count: 7.3%
Dependent repos count: 22.1%
Stargazers count: 27.9%
Average: 28.0%
Forks count: 30.0%
Downloads: 52.6%
Maintainers (1)
Gabra
Last synced: 6 months ago

Dependencies

requires.txt pypi
  • dateutils ==2.8.2
  • numba ==0.55.1
  • numpy ==1.19.1
  • pandas ==1.1.1
  • requests *
  • scikit-learn ==0.23.2
  • scipy ==1.5.2
.github/workflows/codeql-analysis.yml actions
  • actions/checkout v3 composite
  • github/codeql-action/analyze v2 composite
  • github/codeql-action/autobuild v2 composite
  • github/codeql-action/init v2 composite
.github/workflows/pypi-publish.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • pypa/gh-action-pypi-publish v1.5.0 composite