High Frequency Trading: The Battle about Moral Orders
The paper is concerned with the recent shift of moral regimes in financial markets. Particularly, our focus will be on the fast-growing segment of computer-based algorithmic trading (e.g., high frequency trading; HFT). The discussion is based on two case studies: 1) the IPO of Virtu, a high-frequency firm, in April 2015; 2) the recent lawsuit against Barclays (the British bank and seven US exchanges were accused of cheating clients by aligning with HFT traders; however, the case was dismissed by the judge).
Both cases allow the analysis of the shifts of moral orders in modern financial markets. At first sight, the debate about HFT perfectly fits into the topology developed by Fourcade and Healy (2007). Indeed, like all markets, the algo trading segment can be argued to have civilizing, destructive or feeble effects on individuals and society. However, although we can clearly identify the usual controversy between efficiency arguments and assertions about the HFT’s destructive tendencies, the discussion about the merits and detriments of algo trading has some specific traits which we aim to set out in the paper.
In the HFT segment, we observe a shift from face-to-face interactions to the “interaction order of algorithms” (MacKenzie 2015). We agree with Arnoldi’s (2016) claim that we face a new “post-social” regime in which both humans and computerized algos are market actors. In this context, we are not simply dealing with the next stage in the development of market infrastructure but with a principally new situation in the markets. It is not just about humans using technology but about “machines” (computer algorithms) which – parallel to humans – observe markets, interact, initiate and execute decisions and thus participate in financial markets. Thus, morality is not anymore only an issue of individual decision-making but is genuinely embedded in the materiality of markets. In the paper, we seek to demonstrate – in the spirit of “moralized markets” (Fourcade and Healy 2007) – how this change of the social regime is leading to profound shifts in the moral understanding of major market categories such as efficiency, fairness, manipulation and transparency. The central question of the paper will be “How does the new quality of market materiality bring about a change of market moral regimes?”
For example, the trial against Barclays revealed a change in the way market manipulation is interpreted: As long as there is no interference with the market prices of securities, the bank cannot be charged with manipulation (even if there is a negative impact on the price of other market participants’ trades, e.g., front running). Thus, in the HFT regime, the definition of market manipulation has become narrower, indicating a shift towards the legal and political protection of algos. Now, the discrimination of “normal” (not HFT) market participants is labelled “complex order types” and “proprietary data feeds”, implying completely different moral connotations than “conventional” market manipulation. Hence, the Barclays case highlights the new quality of market materiality and thus provides grounds for discussing emerging moral paradigms in the field. At the same time, there are changes in the interpretation of market manipulation for cases in which algorithms – but not humans – are cheated (Arnoldi 2016). Furthermore, the debate around the Virtu IPO demonstrates how efficiency as a vital moral criterion in finance has been contested and transformed in the HFT field.
Thus, based on our case studies, we will show how the increasingly independent market technologies – and the societal discourses around them - co-shape moral rules and shift moral regimes. The aim of the paper is to analyse these shifts with more analytical and empirical details. Particularly, we will reveal moral assumptions underlying the work of algo programmers, algo users, regulators and “normal” market participants. A clear formulation of the moral and ethical dilemmas related to automated decision-making in the modern financial markets is another contribution of the paper. To some extent, this is a pioneering work. Although algo trading and HFT have attracted significant attention of social scientists in recent years, the related moral and ethical issues have not been properly addressed in the literature (articles by Angel and McCabe 2013 and Davis et al. 2013 being an exception). The paper contributes towards closing this research gap.
References:
Angel, James J. and Douglas McCabe (2013). Fairness in Financial Markets: The Case of High Frequency Trading. In: Journal of Business Ethics 112, 585–595.
Arnoldi, Jakob (2016). Computer Algorithms, Market Manipulation and the Institutionalization of High Frequency Trading. In: Theory, Culture & Society, Vol. 33(1), 29–52.
Davis, Michael, Andrew Kumiega, Ben Van Vliet (2013). Ethics, Finance, and Automation: A Preliminary Survey of Problems in High Frequency Trading. In: Science and Engineering Ethics, Volume 19, Issue 3, 851-874.
Fourcade, Marion and Kieran Healy (2007). Moral Views of Market Society. In: Annual Review of Sociology, Vol. 33 (2007), 285-311.
MacKenzie, Donald (2015). How Algorithms Interact: Goffman’s ‘Interaction Order’ in Automated Trading. Working paper, University of Edinburgh.