algo-trader

Trading strategies builder, backtester, and real-time trader.

>pip install algorithmic-trader

Intro

algo-trader is an implementation of an algorithmic trading strategy executor and backtester. Capable of backtesting strategies locally and trading them in real-time via your broker API.

Please be aware that this is a work in progress and the trader is missing external market data and trade providers. If you'd like to use the trader for real-world trading, you'll have to implement your broker API. Although real-time trading is not finished, backtesting is fully functional, so implemented strategies can be backtested and used in real trading when it will be ready.

algo-trader is written in Python, and its current stack composes of:

1. 1.MongoDB as a backend data store for backtesting strategies
2. 2.tulipy - Python bindings for Tulip Indicators.

Used to provide technical indicators calculations.

1. 1.ib_client (Optional) - Python library to communicate with Interactive Brokers gateway. Only needed if you plan on

doing real trading via IB.

Architecture

Pipeline

Pipeline is the basic facilitator of the stream. It’s the orchestrator responsible for reading data from the Source and moving it to the processors in the stream. It has no actual logic except for facilitating the processors. A pipeline and all of its child components are JSON serializable, that is for the system to be able to define, load and save entire pipelines with their configurations on file. This feature is an important one as it can be used as a facade for UI/CLI based runners. Example serialized (and runnable) pipelines can be found in the examples/pipeline-templates directory. Example of loading them into Pipeline and running them using the PipelineRunner can be found in main.py

PipelineRunner

A PipelineRunner will accept an initial list or singular Pipeline, and an optional starting SharedContext. If a SharedContext is not provided during construction, a new one will be initialized. Each Pipeline will be called through run() in the order that it was listed with the previous context. The context will move through each Pipeline allowing for some operations such as loading, caching and validation to occur before data collection and sink.

Sources