A python library that helps assess one's investment portfolio risk.

Below you will find the features and capabilities as I implement them.

Note: only items that are completely implemented are marked complete. If an item is not checked off, it may be only partly implemented.

• Portfolio Object 📁
  • add or remove equity and cash positions
  • create a pandas dataframe that calculates daily returns from positions
  • handle Canadian and American symbols (FX conversion)
  • print portfolio as a JSON object
  • calculate daily portfolio value, percent return, log return
  • create a pandas df containing daily price data for holdings, total value, and benchmark
  • save and load user's portfolios
• Data Object 📊
  • get daily returns for symbols
  • get latest price for symbols
  • get CAD/USD FX data
  • data source agnostic
  • client-side symbol validation
  • Data Sources
    • yfinance
    • tiingo?
    • IEX?
    • use env variables to configure APIs
• Risk Object 📉📈
  • accept portfolio object in class constructor
  • daily average return and volatitily (standard deviation)
  • Daily Beta
  • Sharpe Ratio
  • Correlation Matrix
  • Value at Risk (VaR)
    • historical (1, 3, 5 years)
    • student's t
    • monte carlo?
  • Expected Shortfall (ES/cVaR)
    • historical (1, 3, 5 years)
    • student's t
    • monte carlo?