投资组合回测

投资组合回测是一个 Python 库，用于在 Python 3.7 及更高版本上回测投资组合资产分配。

安装

$ pip install portfolio-backtest
$ pip install PyPortfolioOpt

用法

基本运行

from portfolio_backtest import Backtest

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

高级运行

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': '',
  'Cumulative Return': '160.9%',
  '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': '',
  'Cumulative Return': '102.3%',
  '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': '',
  'Cumulative Return': '53.3%',
  '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': '',
  'Cumulative Return': '48.7%',
  '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%',
  'Cumulative Return': '52.1%',
  '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': '',
  'Cumulative Return': '166.5%',
  '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%',
  'Cumulative Return': '251.3%',
  '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}}]

提供一种方法 (discrete_allocation)，可通过输入最新价格和所需的投资组合规模（本例中为 10,000 美元）将其转换为可供购买的实际分配

from portfolio_backtest import Backtest

bt = Backtest(
    tickers={
        "VTI": 0.6,
        "AGG": 0.25,
        "GLD": 0.15,
    }
)
print(bt.discrete_allocation(total_portfolio_value=10000))

{'Discrete allocation': {'VTI': 28, 'AGG': 21, 'GLD': 9}, 'Funds remaining': '$109.45'}

支持的投资组合

• 您的投资组合
• 分级风险平价投资组合
• 相切投资组合
• 最小方差投资组合
• 最低 CVaR 投资组合
• 半方差投资组合
• 回报最大化 CVaR 投资组合