Innovation In Quality Assurance: What Is The Impact On Trading Technology?

The Technology Services division of LSEG incorporates MillenniumIT, GATElab and Exactpro.
LSEG Reference Test Hamess for Algo Trading Systems
This gives the Group a unique set of software from all three companies at our disposal, which we can use to build test infrastructure for any system. Take testing of trading algos, for example. We can deploy one or several scalable matching engines to function as market simulators. We can utilise GATElab’s algopath or an Exactpro tool called Minirobots to act as market participants. They can both replay some data and at the same time mimic a realistic market impact. In addition, we can have latency and front-running proxies for better test diversity.
It is possible to take the next version of the algo and put it to the test. However, what is the point of running it once? Markets are not deterministic, neither are well-simulated markets. Every time tests are executed, there will be a slightly different result. For this reason, multiple replays are necessary to assess the quality and efficiency of the software.
Software Testing and Trading Technology TrendsThis is where everything falls into place:

  1. Efficient restart and testability to enable unattended test execution
  2. Machine-readable specifications to synchronise all the tools and formally iterate the possible tests
  3. Passive testing capabilities and, potentially, market surveillance to capture and store all the relevant metrics (both P&L and system related ones)

Hypothetically speaking, one can run an infinite amount of tests and execute a wide range of scenarios, except that we all have limited time as well as limited hardware. There are two more quality assurance trends, though, cognitive technology and mutation testing, that allow us selecting an efficient limited subset of tests from an infinite number of possibilities. They are used to find the optimal test scenario subset for a trading platform. They can also be utilised in enhancing the test set along the changes in the system under test and in the surrounding markets.
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