Project goal is to provide reliable execution and very fast market data access. For the development of the next generation algorithmic trading software, that requires access to large data sets, i.e. AI.
Project is still in active development. Expect breaking changes.
To achieve performance necessary for the machine learning algorithms and vast amounts of financial data,
database of choice is Apache Cassandra. Functional scala streaming fs2 and datastax driver 4.0 for cassandra have
little overhead. It is not hard tuned, but native driver and lean code are enough to saturate IBKR gateway.
Interactive Brokers is the largest online broker, that provides good quality, high resolution financial data and
analytics. This is the only broker that had been implemented.
Broker integration is working though the IBC project packaged with ibgateway. I advise on forking and building your own docker image to minimize security risks.
- IbFeed release automatic sinking
ibkrhistoric and realtime bar data intocassandra. You just provide list of contracts to get the data and feed will do the rest. - Ta4j integration for inline technical analysis.
- Docker packaging and build scripts
- Python bindings for cassandra tables
- IbBroker release with back testing
- javacpp integration for using
Tensorflowmodels - insync for python models.
- Docs and examples.
Software is not ready for deployment at the moment.
- Download the TwsApi.jar and fill out the path to it in your
build.sbt - Build the ibgateway image:
- Fill out the
docker-compose-tmlt.yamltemplate and run:docker-compose up -d
TBD
TBD
TBD