"Testing Dark Pool Trading Systems"

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"Organizations adopting Dark Pool Trading Systems need to ensure rapid internal development of algorithms, since conditions that support algorithmic variables can change quickly and requirements can differ greatly from one financial market to the other and from one participant to the other."
Source : AppLabs

Resources Related to Testing Dark Pool Trading Systems:

• Dark Pools of Liquidity (Wikipedia)

Testing Dark Pool Trading Systems

Introduction

The rapid changes in the financial markets have resulted in liquidity being of paramount importance to investors. Investment objectives have changed, technology has changed and there are newer, more innovative products available. The latency reduction concept is also playing a part; every firm is now building or using systems that can match orders within a fraction of second, giving them an edge over their competitors. Almost every brokerage house on Wall Street now operates an internal, electronic trading system that takes incoming trades from clients and tries to find a match internally before turning to other brokers, electronic networks or the exchanges.

These internal systems, known as Dark Pool Trading Systems are intended to trade stocks privately with the objective of liquidating large stock positions at lower costs. Recently, the changes in the financial markets in terms of trading strategies, new product innovations, regulatory requirements and growth in technology have resulted in an increase in trading volumes. In addition to the increased volumes on the exchanges, the volumes of trade on the Dark Pool Trading Systems are growing daily. There are currently 40 Dark Pool Trading Systems operational in the US market. The pictorial representation of a dark pool trade execution is shown as Appendix 1.

The Dark Pool Trading systems, mainly used by the institutional traders who trade in large volumes, help institutional investors in getting more liquidity with lower transaction costs and less transparency. They also help fund managers strategies that are best implemented with the use of algorithmic trading.

High Risk Solution = Rigorous Testing

IAs described above, the systems are complex by nature and also involve significant financial transactions, so the impact of any issues arising out of system downtime is massive. It is therefore imperative that these systems are well tested before their implementation into the production environment. The testing must ensure that all trading strategies, latency issues, regulatory compliances, technological changes and the communication flow between internal and external interfaces have been accounted for and are functioning correctly. To remain competitive, firms need to ensure the rapid internal development of algorithms, since conditions that support algorithmic variables can change rapidly and requirements can differ greatly from one financial markets institution to the next. These requirements need to be tested in advance before implementing them in the real environment. In addition, to quickly identify and address performance issues, firms need the ability to monitor transaction costs, execution statistics and other performance measurements in real time.

Challenges in testing

There are certain challenges when testing Dark Pool Trading Systems:

• Dark Pool Systems are developed mainly to provide more liquidity to the market players. It is very important that real time market scenarios are created in the testing environment with market participation;
• All the functionalities related to the product, business rules and regulations, regulatory compliances, order management and routing criteria etc., must be identified in order to conduct complete end to end testing;
• These systems support different products in different regulatory environments and as such it must be confirmed that these systems satisfy all the regulatory requirements of each environment;
• Each and every execution strategy must be tested;
• The functionality must be identified and complex scenarios for testing must be developed and executed;
• There must be verification of the logs generated during the data flow between the different interfaces;
• As communication between various internal and external interfaces plays a major role for a smooth trading flow in Dark Pool Trading applications, identifying the various interfaces and ensuring an effective communication flow between them becomes crucial.

Testing approach

Considering the complexity of these trading systems in terms of technology, speed, functionality and system performance, it is very important that functional testing is conducted in addition to the gateways testing and performance testing that must be done.

Functional Testing

As these applications are multi-product, multi-segment and multi-user, end to end functionality testing of the application is required. This requires the identification of each functional area, and the subsequent smoke and unit test cases of each need to be developed.

As the Dark Pool Trading Systems are linked with middle office and back office systems for margining, accounting and settlement, it is very important that all these systems are integrated online/offline. So, integration test cases and scenarios covering multiple functionalities need to be developed and executed in the testing environment. The trading opportunity exists only for a fraction of second, therefore scenarios covering multiple trading strategies need to be developed and tested to ensure each strategy works.

In the discovery phase of the functional testing, it is very important to understand the complete product, identify all the functionality and define a test plan. Once the test plan is ready, the testing environment (which will simulate the real time market) needs to be set up. Unit, smoke, regression and integration test cases then need to be authored and reviewed. Once the testing environment and test data are ready, the test cases covering all the functionality need to be authored and reviewed. Once the testing environment and test data are ready, the test cases covering all the functionality need to be executed. The functional testing approach is explained in the below diagram:

Gateways (Interface) Testing:

Dark Pool Trading Systems communicate with various internal and external systems. It is very important that the communication between these interfaces is rapid with no threat of data loss. As these systems are mainly used by institutional traders and bulk executions occur in a short space of time, interface testing plays a crucial role in validating the data flow.

Testing of the interfaces basically ensures the existence of communication between the client and server. The validation of backend messages is done by connecting to the various FIX gateways like DMA, IDCE, etc. The various message tags are also validated for the protocols like FIX (Financial Information Exchange), SIP (Securities Information Processing) and ITS (Inter market Trading System) in the respective gateways.

All the gateway testing is to be done using any of the protocols (usually FIX is used for trading applications) to ensure smooth flow of communication between various gateways associated with the Dark Pool Trading Systems.

Performance Testing:

As the application deals with fast paced transactions, any performance issues can lead to significant loss of investment. It is very important that the application is rigorously tested for its performance.

The performance testing approach is to go through the networks, operating system, databases, application validation levels, number of users, data flow, trading volumes etc. and analyze each of the elements to ensure it is performing at the desired capacity or service levels and determine the elements which are degrading the performance of the system.

As these applications are multi user, it is very crucial to carry out the load testing of these applications which helps in evaluating the performance of the hardware and application with respect to performance and volume targets. Load testing differs from traditional performance testing as it usually refers to the practice of modeling the expected usage of the system by simulating multiple users accessing the program's services concurrently. This is critical to understand prior to implementation.

Conclusions

The volumes of the Dark Pool Trading Systems are increasing every day and there is a huge scope for more organizations to make an entry into this market. To remain competitive, organizations need to ensure the rapid internal development of algorithms, since conditions that support algorithmic variables can change quickly and requirements can differ greatly from one financial market to the other and from one participant to the other. In addition, to give the highest benefit to the client in terms of transactional cost, and also to ensure the highest efficiency in execution, the companies need to have a strong grasp on all system performance. As the risk of failure is catastrophic, all these strategies need to be rigorously tested before implementing them in a live environment.