Tree-Based Algorithmic Backtester

A modular, tree-based algorithmic backtester. The backtester is event-driven, has a historical stock price downloader via Tiingo's API and integrates with TA-Lib to integrate technical analysis into strategies.

Installation

Add algo-backtester to your shards.yml.

TA-Lib

To use the TA-Lib integration, you need to have the TA-Lib already installed. You should probably follow their installation directions for your platform, but some suggestions are included below for reference.

Mac OS X

$ brew install ta-lib

Windows

Download ta-lib-0.4.0-msvc.zip and unzip to C:\ta-lib.

This is a 32-bit binary release. If you want to use 64-bit Python, you will need to build a 64-bit version of the library. Some unofficial (and unsupported) instructions for building on 64-bit Windows 10, here for reference:

1. Download and Unzip ta-lib-0.4.0-msvc.zip
2. Move the Unzipped Folder ta-lib to C:\
3. Download and Install Visual Studio Community 2015
   • Remember to Select [Visual C++] Feature
4. Build TA-Lib Library
   • From Windows Start Menu, Start [VS2015 x64 Native Tools Command Prompt]
   • Move to C:\ta-lib\c\make\cdr\win32\msvc
   • Build the Library nmake

You might also try these unofficial windows binaries for both 32-bit and 64-bit:

https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib

Linux

Download ta-lib-0.4.0-src.tar.gz and:

$ tar -xzf ta-lib-0.4.0-src.tar.gz
$ cd ta-lib/
$ ./configure --prefix=/usr
$ make
$ sudo make install

If you build TA-Lib using make -jX it will fail but that's OK! Simply rerun make -jX followed by [sudo] make install.

Dependencies

• TA-Lib
• Crystal dependencies (installed automatically via shards install):
  • VCR (for caching API requests)
  • halite (HTTP requests)
  • crystal_talib (TA-Lib C bindings)

Usage

require 'algo-backtester'


  bars = TiingoDataDownloader.new.query("AAPL", 3.months.ago, Time.now)

  data = DataHandler.new(stream: bars)

  strategy = Strategy.new("buy_and_hold")
  strategy.set_algo(
    RunMonthlyAlgorithm.new,
    SignalAlgorithm.new(direction: :buy)
  )
  strategy.add_child Asset.new("AAPL")

  backtest = Backtest.new(initial_cash: 1000.0_f64, data: data, strategy: strategy)

  backtest.run

  backtest.statistics.print_summary

Alternatives

• pmorissette's bt Python library
• dirk olbrich's gobacktest Golang package

TODO

• Add more specs (currently specs exist for non-algorithm classes/structs; need to extend to Algorithms)
• Add better documentation
• Add algorithms for more TA-Lib functions (currently just shows SMA as a prototype)
• Compute + print more statistics (currently only shows Sharpe, Sortino and Cumulative Return)

Contributing

1. Fork it (https://github.com/mikeroher/algo-backtester/fork)
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create a new Pull Request

Acknowledgements

• TA Lib Installation instructions from mrjbq7/ta-lib Python Library
• Implementation inspired by the two alternatives listed above.

License