/pinkfish

A backtester and spreadsheet library for security analysis.

Primary LanguagePythonMIT LicenseMIT

pinkfish

08-22-2020: Demonstrate how to use volatility to scale position sizes (see double-7s-portfolio example)
08-21-2020: Add double-7s-portfolio example
08-21-2020: Add volatility indicator and volatility_graph() - see double-7s example
08-21-2020: Add kelly criterian (used to size leverage)- see double-7s-portfolio example
07-27-2020: Add momentum-dmsr example
07-20-2020: Add momentum-pem example - shows how to include indicators in a portfolio
07-20-2020: Add Momentum Indicator
07-16-2020: Add Margin (leverage) cabability

A backtester and spreadsheet library for security analysis.

Why another python backtesting library? How is pinkfish different? Simple, I couldn't find a python backtesting library that allowed me to backtest intraday strategies with daily data. Even simple strategies like 'buying on the close' on the SAME day a 'new 20 day high is set' were not allowed. Additionally, I was put off by the complexity of some of the libraries available, and wanted something simple, that doesn't get in the way, and just allows me to test my trading ideas. One user commented that Pinkfish is "very lightweight and to the point". I didn't set out to write a new backtesting library, but I had to. Daily data is free; minute and tick data are typically not. Using minute and tick data can require hours to run vs seconds for daily data.

Some of the key features of pinkfish:

  • leverages pandas for dataframe, spreadsheet like features
  • leverages matplotlib for making financial graphs
  • uses ta-lib to easily implement technical indicators
  • uses daily data (vs minute or tick data) for intraday trading
  • uses free daily data from yahoo finance
  • simple to use python API
  • backtest single stock/ETF strategy or a portolio (basket of stocks/ETFs)
  • backtest short selling strategies and simulate trading with margin
  • write optimizers to select the best parameters
  • create spreadsheets within Jupyter Notebook by utilizing pandas dataframes and itable formatting

Installation

Follow the installation instructions located at: https://fja05680.github.io/pinkfish/

Examples