Aye Tee nine thousand (not “at nine thousand”).
In automated trading systems, a kill switch is a system feature and/or procedure that can immediately halt and/or disconnect the output of a trading system. Synonymous with kill button.
MIT researchers worked out the physical locations to minimize network latency between a trading system (the small blue dots) and principal exchanges (the big red dots). The graphic is also a good visualization of the extent and integration of global financial markets.
For automated trading, a quality management system includes processes to achieve prudent research, design, development, operation, and control of AT systems. This covers critical activities including quantitative modeling, risk control techniques, backtesting, simulated trading, and probationary trading. This also includes processes for and documentation of software and hardware testing that prove the firm has demonstrated that an AT system functions properly, is operationally safe, and robust to behave acceptably during potential extreme events. Statistical methods for evaluating the stability of AT systems and for real-time monitoring have been developed.
What’s the process the firm should go through to do all these things to justify their belief in the stability of the system? The K|V methodology (i.e. a study of methods) is such a methodology (see Quality Money Management, Elsevier/Academic Press, 2008).
AT 9000 is agnostic with respect to research, development, operation, and control methods. Thus, as a study of methods, K|V is not a prescriptive method itself. Nevertheless, all firms engaged in AT do (or should) engage in the activities described, though not necessarily in sequence of stages and steps shown. Firms should perform in their own study of methods, and define internal processes that satisfy a quality policy and quality objectives. These processes will be unique to each firm and its organizational environment, and potentially to each AT system R&D project. The intent is not to imply uniformity in the structure of an AT firm’s quality management systems or uniformity of documentation.
The ability of AT firms to prove the stability of their systems also depends upon the availability of execution venue (exchange) simulation facilities to fully test those systems. Such simulation facilities must enable testing against all manner of extreme market and infrastructure events.
By achieving a QMS that follows AT 9000, automated trading firms should be able to satisfy their organizational obligations to prove and document that its AT strategies and technologies will operate safely and profitably. There is also a wide body of literature demonstrating that the use of quality management systems improves financial performance.
ISO 9000 refers to a family of standards for quality management systems published by the International Standards Organization (ISO). It defines general activities and artifacts needed by an organization to routinely satisfy requirements of its customers. It is generic and has been applied to all sizes of organizations, industries, and public sector agencies.
A quality management system (QMS) for an organization is a defined process and related artifacts necessary to implement a quality policy. Quality management is the orchestration and control of operations so that they satisfy customer expectations and obligations to stakeholders. The ISO 9000 family of standards is the most widely recognized quality management standard. Many industries where societal safety must be ensured use ISO 9000 as baseline to consistently and efficiently meet customer requirements, regulation, and broad social responsibilities. For example, here are somne industry-specific QMS that use ISO 9000 as a baseline.
- Aerospace: AS 9100
- Automotive Suppliers: ISO/TS 16949 and VDA 6.1
- Chemicals: Dow Chemical Company Quality Management System Manual
- Environmental: ISO 14000 family
- Medical devices: ISO 13485 and IEC 62304
- Food safety: ISO 22000
- Health care: the US National Committee for Quality Assurance (NCQA)
- Telecommunication Systems: TL 9000
- Testing and Calibration Labs: ISO 17025
The SEC and the CFTC have recently lowered the bar for proving market manipulation from intent to recklessness, implying (in the case of AT, necessarily organizational) imprudence or irresponsibility. So, in the case of failure of an AT system, how can the organization prove it was responsible, that it was prudent in its AT research and development (R&D) and operation and control (O&C)? The answer is they were responsible because they followed a recognizably prudent process, one that proved and documented that the firm was justified in believing the future performance (i.e. stability) of its AT system.
AT systems make decisions based on proven research. As such these systems can only modify the outcomes of these decisions using the structures embedded in the software (i.e. real-time risk control).
How do you know your trading system will work? What passes as proven research? The obligation of the AT firm is to prove and document that an AT system’s trading strategy and technology will operate in line with expectations and to specification. Prudence demands that the firm prove that its systems will run in control. This obligation can be satisfied by following a prudent process that justifies expectations in the performance of the AT system.
People involved in AT now have both internal responsibilities to their firm and its profitability and external responsibilities to ensure the safe operation of their systems. What’s problematic is that there are many different, and often competing, views on what the responsibilities are or should be in AT.
AT is an interdisciplinary endeavor requiring the input of traders, computer engineers, and quants. Each of these disciplines has its own perspective. Traders, for example, often take seriously their principal function and obligation to maintain orderly markets. Computer engineers have their own codes which require avoidance of unsafe practices and fail-safe design. (These concepts are most often embedded within the topic of software quality.) Responsibilities in quantitative analysis revolve around staying within the strategic bounds defined in exchange rules and government regulation and, furthermore, are largely thought to be superseded by adherence to mathematical truth.
Additional perspectives are added to the AT sphere by people and organizations outside the AT firm as well. The exchanges have their perspectives, and certainly, as do people in different parts of the world. The following figure shows the perspectives involved in AT:
These perspectives may sometimes be in conflict with each other. Thus, different AT firms may recognize different responsibilities based upon the internal political dominance of one profession. No framework exists in AT that considers cross-disciplinary responsibilities of safety to those who might be harmed—external market participants and society. The new discussion needs to focus on organizational responsibilities. Likewise, as the global trading network spans multiple AT firms, exchanges and countries, it is important also to consider the industry-wide obligations to create confidence in financial markets and their sustainability. The profitability of any individual firm cannot be more important than the safety of the global trading mechanism.
The need for low latency gives rise to a conflict between speed (necessary for profitability) and the inclusion of fail-safe code that may add latency (necessary for safety of external stakeholders). An inherent conflict also exists between minimizing costs and satisfying obligations to, for example, paying for research and development of real-time risk controls and/or redundant systems. As time to market for an AT system matters, production pressure also lead to launch of risky trading systems. The need for profitable AT systems cannot take precedence over the quality—stability and reliability—of the global system.
Each AT system is a piece, a proprietary technological component, of the global trading network. The performance of such components affects potentially all markets, either directly or indirectly. An out-of-control AT system can flood a market or markets with order requests on a time-scale that precludes human intervention. Such flooding can affect market prices, the profitability of other trading firms and exchanges, as well as societal confidence in the sustainability and safety of the financial markets. The strategic or technological failure of an AT system could be catastrophic for these stakeholders in the global trading network.