Building a Money Making High-Frequency Trading System

High-frequency trading system caught in the limelight ever since Goldman Sachs charges against their former employee because of him allegedly stole their Golden Goose - a trading algorithm capable of making consistent profits by trading at high speeds. High-frequency trading systems are often called "mission-critical" or a "too-costly-to-fail" applications for a reasonable cause: they have little allowance for error: one inaccurate high-paced trading functionality can wipe out substantial capital.

Building high-frequency trading systems requires detailed planning and careful implementation. Like any solid technology implementation projects, developing a high-frequency trading system is undergoing a careful stage process below:

• Proper Planning;
• In-depth Analysis;
• Design and Testifying ;
• Implementation and Monitoring; and
• Maintenance and Rework.

When a variant of the system is complete, new issues - which might be costly demand advanced and timely alterations and enhancements to rework on the system which may lead to a new development cycle.

In the planning phase of the process, the management determines the ultimate goals of the system, functionality and operational requirements of the system, including budgets and timelines. A proper planning will always take the proof of concept into study.

The goals and target for the project produced after the proper planning will lead to an established schedules, and estimated budgets. The system functionality, the scope of the project and initial feedback from users and management will be churned out and received approval upon in the in-depth analysis phase.

Heading to in the design phase, the proof of concept is now undergoing a test which may include a lots of back-test and forward testing. A detailed specifications of functionality, may include charts which outline the process, trading rules, screenshots on specific rule of handling, and other output formats such as those of daily reports, and other documents. An objective of the design and testifying stage may include assigning task to specific team in the project for the team of developers at a later stage.

Once the design and testifying of the system is completed, the project finally moves into implementation. A close monitoring is required as this stage involved the assemble of individual modules are have been tested and integrated into a full working module. Necessary rework may be considered if part of the individual module fail to integrate well with the whole system.

High-frequency trading systems make instantaneous decisions to enter and exit positions based on contemporary market conditions and rely on fast execution of transactions. The overall performance of high-frequency systems are particularly susceptible to delays in execution speed and limitations in computing machine's processing power. Both matters may be taken care by the following consideration:

Co-location is an option to tackle the first matter for buy-side customers to further speed up the execution. This is a services that place the computer servers in close proximity to exchanges in order to minimize the physical distance for the order travels to the exchange.

The second matter that issue that impacts performance of high-frequency trading systems is the processing capacity of the servers running the trading programs. High-frequency systems typically analyze every tick across multiple securities and, as a result, consume significant processing power. Therefore one should remove unnecessary application from the computer running the trading program. At the same time, acquire advanced computer or super computer with several gigabytes of memory would definitely help in your high-frequency system performance and avoid lagging in data processing as well.

In conclusion, high-frequency trading is a advanced automation of functions in replacement of the role performed by human employees. When given adequate instructions in the algorithm, computer technology is able to process information and derive trading decision definitely faster than the most advanced human brain.