CTC-Executioner is a tool that provides an on-demand execution/placement strategy for limit orders on crypto currency markets using Reinforcement Learning techniques. The underlying framework provides functionalities which allow to analyse order book data and derive features thereof. Those findings can then be used in order to dynamically update the decision making process of the execution strategy.
The methods being used are based on a research project (master thesis) currently proceeding at TU Delft.
Comprehensive documentation and concepts explained in the academic report
For hands-on documentation and examples see Wiki
orderbook = Orderbook() orderbook.loadFromEvents('data/example-ob-train.tsv') orderbook.summary() orderbook.plot(show_bidask=True) orderbook_test = Orderbook() orderbook_test.loadFromEvents('data/example-ob-test.tsv') orderbook_test.summary()
Create and configure environments
import gym_ctc_executioner env = gym.make("ctc-executioner-v0") env.setOrderbook(orderbook) env_test = gym.make("ctc-executioner-v0") env_test.setOrderbook(orderbook_test)