A C++ HFT Toolkit for Algo Traders
This is the API used to communicate between your trading strategies and other components (market gateways) developed by Roq.
Primary motivations
- You can test without first having to sign a NDA
- Remove barriers
- We publish this open sourced API giving anyone
the free option to implement alternative solutions
- Avoid unnecessary lock-ins
- Easy access to closed source binaries as either
Conda packages or
Docker images
- Lets you focus on your trading strategies
Some of the solutions are free to use, e.g.
roq-clientandroq-influxdb.Other solutions may require you to enter a license agreement with Roq to enable more advanced features, e.g.
roq-coinbase-proandroq-deribit.All solutions are completely free to download.
The gateways are very reasonably priced. Please contact us for further details.
You will not achieve much by compiling this project.
The API is not very useful by itself. You will need some implementation to make it useful.
Roq offers a 100% free implementation named
roq-client.
Head over to Roq Samples
and follow the instrutions there to install the roq-client library.
You can then compile and test some simple examples.
- Ultra low latency
- Single digit microsecond response time
- Very high message throughput
- Only bound by single-message processing time
- Messages communicated to clients using a broadcast design
- Efficient publish-once implementation
- Automatic connection and download management
- Helps you more easily manage state
- Message normalization
- A single unified interface used to access all markets
- Reference data
- Multiplier, tick size, minimum quantity, etc.
- Market data
- L1, L2, trade summary, session/daily statistics, etc.
- Order management
- Create, modify, cancel, ack, update, trade (fill)
- Positions and funds
- Automatically persist all messages to storage device
- With zero impact on trading latency
- Integrate well with popular network kernel-bypass solutions
- Requires epoll support
- Suitable for fully autonomous algorithmic trading
- C++17
- Linux (RHEL, CentOS, Debian, Ubuntu)
- Deployment on same host
- Shared memory for all latency sensitive communication
- Micro-service design
- Busy polling causing 100% CPU usage
- Required to achieve ultra low latency
- CPU isolation, disable hyperthreading, use thread affinity, etc.
are strongly recommended practices
- Therefore not suitable for VM deployment
- Enough CPU cores to support your use-case
Gateways
Support
roq-client- Ultra low latency client-server communication
- In-process simulation framework (including order matching with simulated priority)
roq-simulator- Simulation as a real-time service
roq-influxdb- Export captured events to the InfluxDB time-series database
roq-ansible- Server provisioning using Ansible
- Manage your gateway configurations
roq-vagrant- Test your deployment using Vagrant and VirtualBox
roq-grafana- Grafana dashboards
This image is only an overview
Please refer to the online documentation for a more comprehensive desciption.
The following examples have been tested on a relatively low-powered AMD EPYC 3251 SoC running at 2.5 GHz with hyperthreading disabled. Linux is Ubuntu Server 18.04 LTS with the
isolcpuskernel parameter set. Server is physically located is Switzerland.
The Grafana example dashboard allows you to easily monitor the performance of the gateways.
This is the heartbeat latency between gateways and connected clients.
When hovering, you'll be able to see the attributes of each measurement
We collect a histogram of the measurements. This allows us to visualize e.g. "how many % of the events exceed 5 microseconds" (the tail distribution).
NUMA configuration and thread affinity affects latency. This example shows there are two distinct latencies depending on the deployment.
The gateways will automatically collect profiling information.
When hovering, you'll be able to see the the "cost" of each operation
The cost of processing JSON updates (
ws_l2update) is about 2x that of processing FIX (market_data_incremental_refresh).