Aussie AI

Chapter 4. Trading Engine Components

  • Book Excerpt from "C++ Ultra-Low Latency: Multithreading and Low-Level Optimizations"
  • by David Spuler, Ph.D.

Chapter 4. Trading Engine Components

Overview of Trading Engines

What high-level components does a trading system need? At the top-most level, the sequence in a HFT trading engine goes something like this:

  • Ingest market data (from exchange)
  • Analyze this data
  • Decide whether to trade
  • Submit trade order (to exchange)
  • Risk management and reconciliation

Note that if you work at an exchange, the requirements are reversed, and with an even higher need for mission critical accuracy, but are also somewhat simpler at a high-level:

  • Receive orders from trader clients
  • Matching engine to trigger trade execution
  • Send market data feed out to many traders

Software Components

Each of those components is just a small matter of coding. We do that in C++, of course!

Market data ingestion components include:

  • Exchange network protocol libraries (e.g., UDP multicast client).
  • Market data normalization (converting into your own order objects).
  • Snapshot synchronization support

The central management of orders, sometimes called an Order Management System (OMS), includes various software components:

  • Order book data structure
  • Crossing detection
  • Matching engine (simulated)

A more advanced order book may also have:

  • Order rule support (e.g., FIFO vs pro rata)
  • Special exchange status (e.g., pre-open)
  • Iceberg order detection
  • Market microstructure analysis
  • Generalized order book (beyond limit orders)

Algos are not a big deal in trading, and they’re all published in open-source repositories on the internet (I’m kidding). Here are some of the things you’ll need for your algo engine:

  • Trading decision engine
  • Method or API to specify algos
  • Common primitives library for algos
  • Transpiler from algo language to C++ (also known as “front-office programmers”)
  • Declarative algo specification (yeah, right, dream on!)

Also, since many algo strategies may require data from more than one financial instrument to make a decision to trade, we get to:

  • Multi-instrument order book (multiple assets)
  • Distributed order book management (multiple exchanges)
  • Multi-instrument multi-exchange algo primitives

Trade submission to the exchange is a whole separate ball of wax:

  • Rate limiter (emulated)
  • Pre-trade risk management
  • Trade submission
  • Trade status management
  • Bad trade handling

The risk management and regulatory compliance boffins want their pound of flesh:

  • Risk management engine (pre-trade and post-trade)
  • Position tracking
  • Compliance tracking engine
  • Logging
  • Accounting reconciliation

All of the above stuff is just for live trading. There are some offline C++ capabilities that you’ll need as well:

  • Backtesting — testing if those algo devs can code worth anything.
  • Historical data storage — for backtesting or stress testing.
  • Synthetic data generation — robots do testing better.
  • Compliance reporting — sending it all off somewhere.

If I’ve counted correctly, that’s 33 major software components. So, no matter how great you are at C++, don’t expect to knock out a new trading engine prototype over the weekend.

Low-Level Infrastructure

To implement any of these financial components, you need some helper infrastructure in both hardware and C++ software to make it run fast. Some of the C++ code libraries and templates you might need for speed include:

  • TCP and UDP libraries — advanced network socket programming.
  • Disk and file storage — low latency I/O with memory-mapped files and a custom filesystem.
  • Statistical primitives — going way beyond the average.

Looking more specifically at C++ multithreaded coding components that aid in C++ optimizations:

  • Thread pools — low-latency multithreading.
  • Memory pools — preallocation of memory for objects.
  • In-memory logging — save that data, but not yet.
  • In-memory counters — tracking statistics for performance and accounting.
  • Lock-free queues — forwarding data quickly along the pipeline of components.

Hardware is important, of course, arguably even moreso than the C++ software:

  • Co-located Linux servers (proximity access versus connection via microwave or fiber optics).
  • Network switches
  • NICs (in servers, with kernel bypass capabilities)
  • FPGA servers
  • GPU parallelization
  • Quantum computing (it’s coming!)

The need to communicate over the network also adds:

  • UDP multicast for market data feed ingestion.
  • Kernel bypass (hardware support in NIC hardware, plus C++ code).
  • Inter-site network connectivity (around the world we go!).
  • Connectivity to GPU server farm (e.g., for ML models).
  • Out-of-band networking — host network connections for administration.

Safety, too! Here are some of the custom C++ libraries you may use in low-latency programming:

  • Custom assertions — removeable in production code.
  • Self-testing code — ditto for #if DEBUG.
  • Testing harness — unit tests are someone else’s job.
  • Stress testing — using historical data feeds or synthetic data.
  • Timing and benchmarking — proving your code is faster than the intern’s.
  • Error handling — not using standard C++ exceptions.

There are also various DevOps requirements:

  • Instrumentation — tracing for errors and performance analysis.
  • Monitoring — watch out for red flashing lights.
  • Hardware failure detection — e.g., GPU burn.
  • Kill switch — if it’s redder than red.

That’s another 23 low-level software components to add to the 33 C++ higher-level components in the prior section, and about five major hardware categories. Building all that should take you two weeks!

References

  1. Sourav Ghosh, July 2023, Building Low Latency Applications with C++, Packt Publishing, https://www.amazon.com/dp/1837639353
  2. Charles Cooper, 2021, Fast implementation of an ITCH order book, https://github.com/charles-cooper/itch-order-book
  3. Ronak Chatterjee, 2023, A high frequency trading system built with C++: High performance, low latency high frequency trading system written from scratch in C++, https://github.com/nyarosu/hft
  4. Ranjan (Man of steel), 2025 (updated), Live High-Frequency Trading Exchange Engine, https://github.com/ranjan2829/Live-High-Frequency-Trading-Exchange-Engine
  5. Amitava Biswas, Aug 18, 2023, Designing Low Latency High Performance Order Matching Engine, https://medium.com/@amitava.webwork/designing-low-latency-high-performance-order-matching-engine-a07bd58594f4

 

• Online: Table of Contents

• PDF: Free PDF book download

• Buy: C++ Ultra-Low Latency

C++ Ultra-Low Latency C++ Ultra-Low Latency: Multithreading and Low-Level Optimizations:
  • Low-level C++ efficiency techniques
  • C++ multithreading optimizations
  • AI LLM inference backend speedups
  • Low latency data structures
  • Multithreading optimizations
  • General C++ optimizations

Get your copy from Amazon: C++ Ultra-Low Latency