Research Papers

Creating Test Data for Market Surveillance Systems with Embedded Machine Learning Algorithms

Market surveillance systems, used for monitoring and analysis of all transactions in the financial market, have gained importance since the latest financial crisis. Such systems are designed to detect market abuse behavior and prevent it. The latest approach to the development of such systems is to use
machine learning methods. The approach presents a challenge from the standpoint of quality assurance and the standard testing methods. We propose several types of test cases which are based on the equivalence classes methodology. The division into equivalence classes is performed after the analysis of the
real data used by real surveillance systems. This paper describes our findings from using this method to test a market surveillance system that is based on machine learning techniques.

Olga Moskaleva, Exactpro, LSEG, Russia, Email:
Anna Gromova, Exactpro, LSEG, Russia, Email:

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Reconciliation Testing Aspects of Trading Systems Software Failures

This paper describes the concept of reconciliation testing - a process of using data reconciliation tools to validate the system in parallel with other activities. The authors studied information about two major software failures in electronic trading area: Facebook IPO on NASDAQ and Knight Capital runaway algorithms. This paper contributes to the subject matter by identifying aspects related to data reconciliation during these two events. The authors discuss the balance between automated and manual reactions to discrepancies reported by reconciliation tools and analyze the necessity of introducing reconciliation testing as part of system development life cycle for complex transactional processing systems.

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Dynamic verification of input and output data streams for market data aggregation and quote dissemination systems (Ticker Plant)

Market data aggregation and quote dissemination systems (Ticker Plants) are widely used across the electronic trading industry. A Ticker Plant is responsible for distributing information about multiple execution venues over a normalized protocol. This paper presents a dynamic verification approach for such systems. Based on a set of programs developed by the authors, it allows processing large data sets, including those collected during non-functional testing of trading platforms and using them in real-live production. The paper also outlines benefits and shortcomings of the selected approach for real-time and historical transactions analysis.

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Reference test harness for algorithmic trading platforms

The safety and stability of algorithmic trading software is an ongoing concern for exchanges, market participants and the society in general. Financial regulators
worldwide are trying to create effective rules to prevent selfenforced market volatility and technology crashes caused by computer-aided trading. Specifying relevant requirements for dynamic software verification of algorithmic trading platforms remains is an on-going task. Yet, there has been little progress to date in locating efficient and commonly accepted approaches. This paper introduces a reference test harness implementation for algo trading platforms created by the authors.

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High Performance Load Generator for Automated Trading Systems Testing

The growing volume of orders generated by HFT (high-frequency trading) systems has posed a challenge of conducting exchange and brokerage systems testing in production-like environments. Specialized testing tools are used to ensure quality of high load trading systems with high availability. The main requirement for such tools is that they
should be capable of creating realistic, high loads using limited hardware infrastructure. This article describes a load injection tool developed for testing automated trading systems and an approach that ensures high performance.

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Trading Day Logs Replay Limitations and Test Tools Applicability

This paper is an experience report on replaying full trading day production log files for dynamic verification of securities exchange matching engines. Three types of test automation tools developed in-house are described along with their characteristics. The paper analyzes various approaches to reproduce processes and scenarios observed in the systems during their production usage. The applicability and limitations of these approaches are also considered. The authors point out that for most complex distributed real-time trading systems it is extremely difficult to obtain an identical behavior using production logs replay via external gateways. It might be possible to achieve this by implementing additional instrumentation inside the exchange system’s core. The authors assume however that such an intrusion has limited value and should not be prioritized
over other, more appropriate, test design methods for testing such systems.

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