Skip to main content

portfolio-backtest is a python library for backtest portfolio asset allocation on Python 3.7 and above.

Project description

portfolio-backtest

PyPI License: MIT codecov Build Status PyPI - Python Version Downloads

portfolio-backtest is a python library for backtest portfolio asset allocation on Python 3.7 and above.

Installation

$ pip install portfolio-backtest PyPortfolioOpt

Usage

basic run

from portfolio_backtest import Backtest

Backtest(tickers=["VTI", "AGG", "GLD"]).run()

tangency-portfolio.png minimum-variance-portfolio.png hierarchical-risk-parity-portfolio.png minimum-cvar-portfolio.png cumulative-return.png

advanced run

from portfolio_backtest import Backtest
import pprint

bt = Backtest(
    tickers={
        "VTI": 0.6,
        "AGG": 0.25,
        "GLD": 0.15,
    },
    target_return=0.1,
    target_cvar=0.025,
    data_dir="data",
    start="2011-04-10",
    end="2021-04-10",
)
pprint.pprint(bt.run(plot=True))
[{'Annual volatility': '10.9%',
  'Conditional Value at Risk': '',
  'Expected annual return': '9.6%',
  'Sharpe Ratio': '0.70',
  'portfolio': 'Your Portfolio',
  'tickers': {'AGG': 0.25, 'GLD': 0.15, 'VTI': 0.6}},
 {'Annual volatility': '6.3%',
  'Conditional Value at Risk': '',
  'Expected annual return': '7.0%',
  'Sharpe Ratio': '0.79',
  'portfolio': 'Tangency Portfolio',
  'tickers': {'AGG': 0.67099, 'GLD': 0.0, 'VTI': 0.32901}},
 {'Annual volatility': '4.3%',
  'Conditional Value at Risk': '',
  'Expected annual return': '4.3%',
  'Sharpe Ratio': '0.53',
  'portfolio': 'Minimum Variance Portfolio',
  'tickers': {'AGG': 0.91939, 'GLD': 0.00525, 'VTI': 0.07536}},
 {'Annual volatility': '4.0%',
  'Conditional Value at Risk': '',
  'Expected annual return': '4.1%',
  'Sharpe Ratio': '0.51',
  'portfolio': 'Hierarchical Risk Parity Portfolio',
  'tickers': {'AGG': 0.89041, 'GLD': 0.05695, 'VTI': 0.05263}},
 {'Annual volatility': '',
  'Conditional Value at Risk': '0.5%',
  'Expected annual return': '4.2%',
  'Sharpe Ratio': '',
  'portfolio': 'Minimum CVaR Portfolio',
  'tickers': {'AGG': 0.93215, 'GLD': 0.0, 'VTI': 0.06785}},
 {'Annual volatility': '7.7%',
  'Conditional Value at Risk': '',
  'Expected annual return': '10.0%',
  'Sharpe Ratio': '1.04',
  'portfolio': 'Semi Variance Portfolio (target return 10.0%)',
  'tickers': {'AGG': 0.39504, 'GLD': 0.0, 'VTI': 0.60496}},
 {'Annual volatility': '',
  'Conditional Value at Risk': '2.5%',
  'Expected annual return': '13.3%',
  'Sharpe Ratio': '',
  'portfolio': 'Return Maximize CVaR Portfolio (target CVaR 2.5%)',
  'tickers': {'AGG': 0.08851, 'GLD': 0.0, 'VTI': 0.91149}}]

advanced-your-portfolio.png advanced-tangency-portfolio.png advanced-minimum-variance-portfolio.png advanced-hierarchical-risk-parity-portfolio.png advanced-minimum-cvar-portfolio.png advanced-return-maximize-cvar-portfolio-(target-cvar-2.5%).png advanced-semi-variance-portfolio-(target-return-10.0%).png advanced-cumulative-return.png

Supported Portfolio

  • Your Portfolio
  • Hierarchical Risk Parity Portfolio
  • Tangency Portfolio
  • Minimum Variance Portfolio
  • Minimum CVaR Portfolio
  • Semi Variance Portfolio
  • Return Maximize CVaR Portfolio

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

portfolio-backtest-0.1.16.tar.gz (6.1 kB view hashes)

Uploaded Source

Built Distribution

portfolio_backtest-0.1.16-py3-none-any.whl (5.3 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page