README
aat is an asynchronous, event-driven framework for writing algorithmic trading strategies in python with optional acceleration in C++. It is designed to be modular and extensible, with support for a wide variety of instruments and strategies, live trading across (and between) multiple exchanges, fully integrated backtesting support, slippage and transaction cost modeling, and robust reporting and risk mitigation through manual and programatic algorithm controls.
Like Zipline and Lean, aat exposes a single strategy class which is utilized for both live trading and backtesting. The strategy class is simple enough to write and test algorithms quickly, but extensible enough to allow for complex slippage and transaction cost modeling, as well as mid- and post- trade analysis.
aat is in active use for live algorithmic trading on equities, commodity futures contracts, and commodity futures spreads by undisclosed funds.
Overview
A complete overview of the core components of aat is provided in the GETTING_STARTED file.
Internals
aat's engine is composed of 4 major parts.
- trading engine
- risk management engine
- execution engine
- backtest engine
Trading Engine
The trading engine initializes all exchanges and strategies, then martials data, trade requests, and trade responses between the strategy, risk, execution, and exchange objects, while keeping track of high-level statistics on the system