Social media commentary, satellite imagery and GPS data are a part of ‘alternative data’, that is, data that originate outside of the standard repertoire of market data but are considered useful for predicting stock prices, detecting different risk exposures and discovering new price movement indicators. With the availability of sophisticated machine-learning analytics tools, alternative data are gaining traction within the investment management and algorithmic trading industries. Drawing on interviews with people working in investment management and algorithmic trading firms utilizing alternative (...) data, as well as firms providing and sourcing such data, we emphasize social media-based sentiment analytics as one manifestation of how alternative data are deployed for stock price prediction purposes. This demonstrates both how sentiment analytics are developed and subsequently utilized by investment management firms. We argue that ‘alternative data’ are an open-ended placeholder for every data source potentially relevant for investment management purposes and harnessing these disparate data sources requires certain standardization efforts by different market participants. Besides showing how market participants understand and use alternative data, we demonstrate that alternative data often undergo processes of prospecting and assetization. We further contend that the widespread embracement of alternative data in investment management and trading encourages a financialization process at the data level which raises new governance issues. (shrink)

Certain strands of contemporary media theory are concerned with the ways in which computational environments exploit the ‘missing half-second’ of human perception and thereby influence, control or exploit humans at an affective level. The ‘technological unconscious’ of our times is often understood to work at this affective level, and high-frequency trading is regularly provided as a primary illustrative example of the contagious dynamics it produces. We challenge and complicate this account of the relation between consciousness, affect and media technologies by (...) drawing on the recent work of N. Katherine Hayles and by focusing in detail on the ways in which the ‘costs of consciousness’ are accounted for and negotiated in high-frequency trading. We suggest that traders actively develop modes of awareness accounting for the costs of consciousness, and that the necessary ‘stupidity’ of high-frequency trading algorithms as well as competition pose limits to the full automation of financial markets. (shrink)

This article suggests that Facebook embodies a new logic of capitalist governance, what has been termed the ‘social logic of the derivative’. The logic of the derivative is rooted in the now dominant financial level of the capitalist economy, and is mediated by social media and the algorithmic processing of large digital data sets. This article makes three precise claims: First, that the modus operandi of Facebook mirrors the operations of derivative financial instruments. Second, that the algorithms that Facebook uses (...) share a genealogy with those of derivative financial instruments – both are outcomes of the influence of the ‘cyber sciences’ on managerial practice in the post-war years. Third, that the future potential of Facebook lies in its ability to apply the logic of derivatives to the financial valuation of ordinary social relations, thus further extending the process of financialization of everyday life. (shrink)