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Ethics, Finance, and Automation: A Preliminary Survey of Problems in High Frequency Trading

Abstract

All of finance is now automated, most notably high frequency trading. This paper examines the ethical implications of this fact. As automation is an interdisciplinary endeavor, we argue that the interfaces between the respective disciplines can lead to conflicting ethical perspectives; we also argue that existing disciplinary standards do not pay enough attention to the ethical problems automation generates. Conflicting perspectives undermine the protection those who rely on trading should have. Ethics in finance can be expanded to include organizational and industry-wide responsibilities to external market participants and society. As a starting point, quality management techniques can provide a foundation for a new cross-disciplinary ethical standard in the age of automation.

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Notes

  1. By “automated trading”, we mean any computerized system. We consider high-frequency trading to be a subset of automated trading. High-frequency trading systems include automated stock and option market-making systems, index arbitrage and equity long-short systems. Automated trading is a broader term encompassing high-frequency trading as well as longer term strategies such as statistical arbitrage, merger arbitrage, and execution systems for volume-weighted average price. What all automated trading systems have in common is that technology (computers, mathematical modeling, and the like) is a source of competitive advantage.

  2. In this paper, we consider the automation of trading decisions and their execution in electronic markets. However, a subset or adjunct of automated trading (and just as important) is the use of automated algorithms that guide financial decisions that do not result in computer-generated executions, such as theoretical pricing and risk management algorithms. We do not address these forms of financial automation specifically, but recognize that our conclusions may apply to algorithms as well.

  3. Quality arbitrage occurs when one automated market participant knows the automated (therefore, deterministic) behavior of other market participants—trading firm, clearing firm, exchange—and profits by exploiting that behavior. For example, if firm A’s trading system knows how firm B’s trading system will react under certain circumstances, firm A’s trading system can cause that circumstance to occur repeatedly and profit at the expense of firm B. Quality arbitrage can also occur if firms A and B use identical strategies, but gain market access through technologies with varying degrees of speed or quality. Further, if one exchange has inferior technology, a trading firm may be able exploit that inferiority relative to other exchanges/execution venues. Thus, at each point of trade selection and execution, quality may be the determining factor for sustainable competitive advantage.

  4. “Financial engineering” is generally synonymous with mathematical finance, financial mathematics, quantitative finance, or computational finance. A survey of the codes of ethics of the relevant organizations—International Association of Financial Engineers, Professional Risk Managers International Association, and the Global Association of Risk Professionals—uncovered no discussion of the ethics of financial automation. Programs in financial engineering are not accredited by ABET. Hence, the quotation marks around the term. Generally, “financial engineers” are not engineers strictly speaking.

  5. By “computer engineers”, we mean to include programmers, software quality engineers, and network engineers—many of whom will be computer scientists rather than engineers strictly speaking.

  6. DMA refers to the facilities that allow a financial institution to route orders to the exchange order book without first passing through its clearing member or broker’s technology for pre-trade approvals.

  7. Prudence has long been an ethical obligation in financial services. The Prudent Man Rule is an outgrowth of the landmark Harvard College v. Amory case in Massachusetts in 1830.

  8. In the age of automated finance, the definition of trader is evolving. We do not pretend to know its future—or even its exact contours today.

  9. There is also a Software Engineering Code of Ethics and Professional Practice (ACM/IEEE 1999), the result of a joint effort of the ACM and IEEE.

  10. The engineering literature has examined behavioral aspects of systems monitoring and adjustment. Adaptive fail-safe controllers have proven to manage high-speed machines better than human controllers. The research of Suh and Cheon (2002) and Williams and Davies (1986) are notable in this regard. Bilson et al. (2010) and Hassan et al. (2010) have argued that an R&D process should prove stability and establish quantified limits for control of trading systems.

  11. By culture, we simply mean a distinctive way of doing things. Not only nations and regions have cultures, but organizations, professions, and even occupations have them.

  12. Mason asked Lund to think like a manager rather than an engineer before Lund approved the launch of the Challenger space shuttle after initially opposing it as Vice President of Engineering (Davis 1991)

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Davis, M., Kumiega, A. & Van Vliet, B. Ethics, Finance, and Automation: A Preliminary Survey of Problems in High Frequency Trading. Sci Eng Ethics 19, 851–874 (2013). https://doi.org/10.1007/s11948-012-9412-5

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Keywords

  • High-frequency trading
  • Automation
  • Ethics
  • Quality management
  • Engineering