The politics of algorithmic finance

Abstract

This dystopic and disturbing prophecy is the company slogan of the (fictional) Geneva-based hedge fund Hoffmann Investment Technologies, as revealed in the concluding chapter of Robert Harris's 2011 sci-fi thriller The Fear Index. Briefly stated, The Fear Index tells the story of a scientist and hedge fund owner, Dr Alexander Hoffmann, whose ground-breaking invention, the VILAX-4 machine learning algorithm, gradually escapes from the company's and thus its creator's control. Although the trading algorithms used in today's financial markets are not sophisticated enough to threaten the global economy, Harris's novel does address some of the political, economic, and regulatory issues emanating from the growing automation of financial market trading. The financial sector has been heavily criticised for some aspects of its commercial 'ingenuity' which gave rise to the 2008 financial crisis, notably the creation of highly complex and bubble-instigating financial products such as collateralised debt obligations (CDOs), credit default swaps, and subprime mortgages (see, for example, Langley 2010). If the crisis helped shed light on an overly innovative financial sector, the recent propagation of trading algorithms has sparked debates about the consequences of the increased automation and, more broadly, the changing face of trading in today's financial markets. What becomes of the human trader in this increasingly automated market? Trading algorithms are clearly faster, more alert, and more capable of processing large quantities of information than their human counterparts (Kunz and Martin 2013: 137). Another obvious yet crucial advantage of algorithms over human traders is that they do not get carried away by emotion, which Harris's protagonist, Dr Hoffmann, regards as the defining difference between the perfectly rational trading algorithm and the feeble human actor (Harris 2012: 84). This helps to underline that the rise and dominance of algorithmic trading has resituated and altered the practices of financial market participants (including traders), thereby also reconfiguring the power relations and institutional framework which constitute the politics of the market (Lenglet 2011: 47). Trading algorithms are, in this sense, 'political objects' (Lenglet 2011: 51), giving rise to concerns about the stability of the global economy, global politics, and the reach and scope of market regulation, as well as problematising the diminishing role of human traders in the trading process (I get back to how Harris aptly unfolds the interconnectedness of global finance, economy and politics in The Fear Index). One of the most pertinent political concerns about algorithmic trading is the fact that it has turned the global securities markets into a regulatory nightmare. Since, according to Karen Kunz and Jena Martin, the 'very nature of the market has been fundamentally changed', market regulations have to change accordingly, and regulators arguably need to reorient their attention towards trading algorithms (Kunz and Martin 2013: 136; Snider 2014: 757). Instead of focusing on the regulatory challenges posed by algorithmic finance, though, this review essay examines its political implications - the broader meaning of the way in which the changed relationships between human traders and algorithms have changed former trading practices and market configurations. These changing dynamics are analysed via a reading of Harris's imaginative account of financial capitalism 'gone rogue' in the financial district of Geneva. Besides examining how algorithms colonise the market space formerly occupied and controlled by human traders, the review essay draws on ongoing IR discussions of popular culture, and the potential contribution of popular imaginaries (in this case, literary fiction) to an understanding of politics and the political. Pop culture is said to do more than merely reflect established political structures; it affects the construction of the political, just as the political is reflected in pop culture (Grayson, Davies and Philpott 2009). Compared to what could crudely be called 'conventional empirical IR theory', pop-cultural accounts of politically contested phenomena (including the automation of financial market trading) allows nuances to surface which are difficult to grasp empirically (Moore 2010: 312, 316). In the process, they help us to understand some political aspects (such as the social, psychological, cultural and historical underpinnings) of a complex phenomenon such as algorithmic finance.